ML

机器学习

机器学习AI算法工程

AI之禅 机器之心 ATYUN订阅号 AI科技大本营的专栏 BestSDK 云+直播

平台

ML

NVIDIA(u2b, )	NVIDIA Developer(u2b, s, CUDA, doc, )
RE•WORK(u2b, )	MNN - 深度神经网络推理引擎(git, 书栈, )
Scientific Computing and Artificial Intelligence u	MIT OpenCourseWare(u, s, tw, ins, fb, AI, CS, math, )
brilliant(v, )	Theano(s, git, pypi, 书栈, )
XLearning(git, 文档, 书栈, )	Towards Data Science(s, )
天善智能学院(s, u, )	CityAge Media(u, )
SF Python u	Zfort Group(u, )
KDD2018 video u	Компьютерные науки计算机科学(u, )
Serrano.Academy u	臺大科學教育發展中心CASE u
机器学习 知乎话题	中国人工智能学会 s CAAI wb
engineerknow mechanical coder u	台灣機器學習有限公司 u
Microsoft(s, research, u, )	MOPCON u
Vivian NTU MiuLab u	Cartesiam u
Stanford MLSys Seminars u	Center for Language and Speech (CLSP) @ JHU u
Stanford HAI u
Machine Learning at Berkeley u	The Alan Turing Institute u
Tübingen Machine Learning u 图宾根大学机器学习	MLSS Iceland 2014 u Machine Learning Summer School

Quora
Advances in AI(quora, )	Training Data for Machine Learning(quora, )
ABC of DataScience and ML(quora, )	Machine Learning: ML AI(quora, )
Python & Machine Learning(quora, )	HW accelerators eating AI(quora, )
Machine Learning(quora, )	Machine Learning 93(quora, )
	Data science must needed(quora, )
Psychology of Machines(quora, )
Future TEC.(quora, )
Global AI Platform(quora, )

AMLD
AMLD指的是Applied Machine Learning Days（应用机器学习日），是一个面向机器学习和人工智能领域的国际会议，也是一个非营利性组织。该组织致力于促进机器学习和人工智能技术的应用和发展，并为学术界、工业界和政府机构提供交流和合作的平台。AMLD成立于2016年，总部位于瑞士日内瓦。该组织定期举办国际会议、研讨会和培训课程，吸引了来自全球各地的学者、研究人员、工程师、企业家和政府官员参加。
AMLD Africa u Applied Machine Learning Days u

北风网Python人工智能 砖家王二狗

北风网Python人工智能-1-数学基础

北风网Python人工智能-2-Python基础

北风网Python人工智能-3-Python高级应用

北风网Python人工智能-4-机器学习

北风网Python人工智能-5-数据挖掘与项目实战

北风网Python人工智能-6-深度学习

北风网Python人工智能-7-自然语言处理

北风网Python人工智能-8-图像处理

北风网的大数据时代的Python金融应用实战

麦子人工智能视频教程 砖家王二狗

麦子人工智能视频教程(第一阶段：Python数据分析与建模库)

麦子人工智能视频教程(第二阶段：机器学习经典算法)

麦子人工智能视频教程(第三阶段：机器学习案例实战)

DL

	Carnegie Mellon University Deep Learning u
Deep Learning(quora, )	Supervisely u

Data Science

Ping Data Science(quora, )	Data Engineering Minds(quora, )
Data Sciences - Analytics(quora, )	Data Analytics or EnGines(quora, )
	Data Science in Marketing(quora, )

UP主

ML up

迪哥有点愁 B, git bt 迪哥谈AI B 唐宇迪	sentdex(u2b, pythonprogramming, )
Data Application Lab u aipin	莫烦Python(u2b, )
将门-TechBeat技术社区(u2b, )	DeepMind(u2b, )
华校专(s, git, AI算法工程师手册, )	Knowing AI u2b B B更多
Dan Van Boxel(u2b, )	Pi School(u2b, )
Siraj Raval(u2b, )	Marc McLean(u2b, )
Sam Gu(u2b, )	Geoff Gordon(u2b, )
AiPhile u	Mark Jay(u2b, )
Arxiv Insights(u2b, )	AI壹号堂(B, )
yingshaoxo's lab(u2b, )	SuperGqq(s, )
Jeff Heaton(u, git, )	红色石头(s, ZH, 微信公众号/微博：AI有道)
Pascal Poupart(u, )	艾哈迈德·巴齐（Ahmad Bazzi)(u, )
Two Minute Papers(u, )	Kai博士(u, )
Daniel Bourke(u, )	Manisha Sirsat(quora, )
刘先生(u, )	Nicholas Renotte(u, )
DigitalSreeni u	Applied AI Course(u2b, )
CodeEmporium u	帅帅家的人工智障(B, )
李宏毅Hung-yi Lee(s, u, )	深度碎片(B, )
DeepPavlov u	啥都会一点的研究生(B, )
Math4AI(B, )	Acsic People(u, )
Pantech eLearning(u, )	爱可可-爱生活/Guang Chen/fly51fly/B u git
AI Prism(u, )	StatQuest with Josh Starmer(u, )
The Coding Train u	魏博士人工智能　抖音号： Dr.WeiAI
李文哲 抖音号： vince88888	AI有啥用 抖音号： 2016078732
AI技术资讯 抖音号： JiuhuiLi2020	好玩的AI 抖音号： haowandeai
算法工坊 抖音号： ALGHUB	阿里达摩院扫地僧 抖音号： 54saodiseng
小乔斯在洛杉矶 抖音号： Joyceni0610	MITCBMM u
FunInCode u B	王木头学科学 u B
硅谷吴军　抖音号： wujun001	The AI Epiphany u
技术喵　ｕ	珂学原理 u
高怡宣老師　ｕ	白手起家的百万富翁 u
William　ｕ	李政軒　ｕ
人工智能之趋势 u	Luis Serrano u
徐亦达 u	Art of the Problem u
Shusen Wang u en	Artificial Intelligence - All in One u
跨象乘云 u primo B	Weights & Biases u doc s v
AICamp u	卍卍子非鱼卍卍 B
Scc_hy git csdn	codebasics u
人工智慧與數位教育中心 NCCU AIEC u	解密遊俠 u
贪心学院 Greedy AI u	Min Yuan u
hashtag/machinelearningforbeginners	深度之眼官方账号 u
Learning AI u	財團法人人工智慧科技基金會 u
千锋教育 u	做大饼馅儿的韭菜 zh
机器学习-白板推导系列 shuhuai008 u B	容噗玩Data u
Justin Solomon u	WsCube Tech! ENGLISH u
Machine Learning with Phil u	就是不吃草的羊 B
Artificial Intelligence and Blockchain u	Colin Galen u
Si磕AI论文的女算法 抖音号：49634887878	When Maths Meet Coding u
Artificial Intelligence Society u	Dr. Data Science u
Pista Academy u 波斯语	Parallel Computing and Scientific Machine Learning u
William u csdn	Machine Learning Street Talk u
Dr Alan D. Thompson u	Jeremy Howard u
Artem Kirsanov u	James Briggs u
論文導讀 工gin師	TeachMe AI u
Priya Bhatia u	大白话AI u
Find Interesting AI u	Open Data Science u
炮老师AICG小课堂 u

arXiv
arXiv是由康奈尔大学运营的一个非营利性科学论坛，通常科学家在论文正式发表前会预先发到arXiv上防止自己的理论被剽窃．

DL up

飞桨Paddle(s, B, OCR(git), book, 文档, )
Deeplearning.ai(u2b, )	Sung Kim(u2b, )
Leonardo Zhou(u2b, )	Caffe2(书栈, )
deeplearningbook(s, Taro, )	DL4J(书栈, )
VisualDL(文档, 书栈, )

	Alan Tessier u
Alexander Amini(u, )	deeplizard(u, )
Alex Smola(u2b, )	Lex Fridman(u2b, )
Alena Kruchkova(u2b, )	Alex(u2b, )
andrej karpathy	吴恩达
ryan adams	yisong yue
Rachel Thomas(u2b, )	Ian Goodfellow
Deep Sort(blog, )	Yannic Kilcher(u, git(v), )
Tien-Lung Sun u	茶米老師教室 u
AI转转转 u

fast.ai
git,
fastbook(git, 书栈, )
Jeremy Howard — The Story of fast.ai and Why Python Is Not the Future of ML Weights & Biases
Jeremy Howard: fast.ai Deep Learning Courses and Research | Lex Fridman Podcast #35

Data Science up

Data Professor(u, fb, medium, git, )	Data Science Conference(u, )
Data Science Courses(u2b, )	APMonitor.com u
Ken Jee u	小旭学长 u
Pepcoding u	Amulya's Academy u
	Yoav Freund u

ai工具

火線班迪 u 阿石OMP u 肥拉超漫flcman u

框架

Long Liangqu

深度学习与PyTorch教程 Long Liangqu 网易云课堂

深度学习与TensorFlow 2入门实战 Long Liangqu 网易云课堂 味道

深度学习与TensorFlow 2 Long Liangqu

magnet:?xt=urn:btih:F60CCA8F091866C1F6F35460882285386719588B&dn=%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E4%B8%8EPyTorch%E5%85%A5%E9%97%A8%E5%AE%9E%E6%88%98%E6%95%99%E7%A8%8B

2022 Version of Applications of Deep Neural Networks for TensorFlow and Keras (Washington University in St. Louis) Jeff Heaton
I built the same model with TensorFlow and PyTorch | Which Framework is better? Python Engineer
AI框架基础 ZOMI

Tensorflow

TensorFlow(site, install, pip, gpu, 教程, 指南, API, u, models, blog, medium, 书栈(1, 2, ), )
jikexueyuanwiki/tensorflow-zh TensorFlow官方文档中文版 s 过时
TensorFlow 2.x Insights EscVM
TensorFlow2.0 入门到进阶 刘先生
【北京大学】人工智能 Tensorflow2.0 刘先生 bdy mocm
人工智能 Tensorflow 视频教程全集| 5 小时从入门到精通 刘先生
TensorFlow Tutorial 修炼指南 Albert's Code Lab Creat Code Build
Tensorflow框架 开发者学堂
TensorFlow快速入门与实战 极客时间
TensorFlow 2项目进阶实战 极客时间
Tensorflow Object Detection in 5 Hours with Python
TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial freeCodeCamp 6:52:07 Tech With Tim
TensorFlow 2.0 Crash Course freeCodeCamp
机器学习从零到一　一　二　三　四　TensorFlow
TensorFlow Lite 视频系列教程　TensorFlow
深度学习应用开发-TensorFlow实践 刘先生
TensorFlow 2.0 李政轩
TensorFlow Lite 视频系列教程 TensorFlow
TensorFlow 2 Beginner Course Python Engineer
Deep Learning for JavaScript Hackers | Use TensorFlow.js in the Browser Venelin Valkov
Made with TensorFlow.js TensorFlow
TensorFlow And Keras Tutorial | Deep Learning With TensorFlow & Keras | Deep Learning | Simplilearn
联想拯救者R9000P安装Ubuntu 21.04系统及运行TensorFlow1.X代码 csdn
Tensorflow CloseToAlgoTrading
Google's Machine Learning Virtual Community Day TensorFlow
TensorFlow Lite for Edge Devices - Tutorial freeCodeCamp
Android Apps TheCodingBug YOLOv4 TFLite Object Detection Android App Tutorial Using YOLOv4 Tiny, YOLOv4, and YOLOv4 Custom
[Tutorialsplanet.NET] Udemy - TensorFlow 2.0 Practical Advanced
深度学习框架Tensorflow2实战 DayDayUP 唐宇迪
Learn TensorFlow and Deep Learning (beginner friendly code-first introduction) Daniel Bourke Learn TensorFlow and Deep Learning fundamentals with Python (code-first introduction) Part 1/2 Daniel Bourke 10:15:27 Learn TensorFlow and Deep Learning fundamentals with Python (code-first introduction) Part 2/2 Daniel Bourke 3:57:54
Aladdin Persson u
Deep Learning for Computer Vision with TensorFlow – Complete Course freeCodeCamp 1:13:16:40 colab

PyTorch

PyTorch u s doc tw fb medium PyTorch(github, u, s, 中文教程, )
pytorch/tutorials s the official PyTorch tutorials
PyTorch for Deep Learning & Machine Learning – Full Course freeCodeCamp 1:01:37:25
Getting Started With PyTorch (C++) Alan Tessier
Image Classification using CNN from Scratch in Pytorch AI-SPECIALS
Neural Network Programming - Deep Learning with PyTorch deeplizard PyTorch - Python Deep Learning Neural Network API
Pytorch基础入门 覃秉丰 git
PyTorchZeroToAll (in English) Sung Kim
PyTorch ClarityCoders
PyTorch for Deep Learning - Full Course / Tutorial freeCodeCamp 9:41:39
Deep Learning and Neural Networks with Python and Pytorch sentdex
TorchScript and PyTorch JIT | Deep Dive PyTorch
PyTorch and Monai for AI Healthcare Imaging - Python Machine Learning Course freeCodeCamp
PyTorch Tutorials - Complete Beginner Course Python Engineer
Introduction to PyTorch Tensors Coding Epocs
PyTorch - Deep Learning Course | Full Course | Session -1 | Python Tangoo Express
Getting Started With PyTorch (C++) Alan Tessier
PyTorch on Apple Silicon | Machine Learning Alex Ziskind
Invited Talk: PyTorch Distributed (DDP, RPC) - By Facebook Research Scientist Shen Li
7 PyTorch Tips You Should Know Edan Meyer
Learn PyTorch for deep learning in a day. Literally. Daniel Bourke 1:01:36:57
PyTorch Transfer Learning with a ResNet - Tutorial langfab
How to Install PyTorch GPU for Mac M1/M2 with Conda Jeff Heaton
Saving and Loading a PyTorch Neural Network (3.3) Jeff Heaton
I Built an A.I. Voice Assistant using PyTorch - part 1, Wake Word Detection The A.I. Hacker - Michael Phi
bentrevett/pytorch-seq2seq PyTorch Seq2Seq
PyTorch 深度學習快速入門教程（絕對通俗易懂）| 土堆教程 我是土堆
Python机器学习算法与实战 Adam Sun zh Python在机器学习中的应用 Adam Sun Daitu/Python-machine-learning PyTorch深度学习入门和实战 Adam Sun
Machine Learning Course With Python Siddhardhan
Deep Learning With PyTorch - Full Course Python Engineer
PyTorch Beginner Series PyTorch
Pytorch Krish Naik
PyTorch Tutorials (2022) Mr. P Solver
Pytorch Krish Naik
PyTorch2.0 ZOMI
Pytorch+cpp/cuda extension 教學 tutorial AI葵
Aladdin Persson u
Install PyTorch for Windows GPU Jeff Heaton

Deep Learning with PyTorch: Zero to GANs freeCodeCamp
PyTorch Basics and Gradient Descent | Part 1 of 6
PyTorch Images and Logistic Regress | 2 of 6
Training Deep Neural Networks on GPUs | Part 3 of 6
Image Classification with Convolutional Neural Networks | Part 4 of 6 bk
Data Augmentation, Regularization, and ResNets | 5 of 6
Image Generation using GANs | Part 6 of 6
PyTorch: Zero to GANs Dhanabhon Subha-asavabhokhin
Deep Learning with PyTorch: Zero to GANs Jovian

Keras

Keras(s, git, Sequential, b, 文档(en, zh, ), )

Keras - Python Deep Learning Neural Network API deeplizard
Keras with TensorFlow Course - Python Deep Learning and Neural Networks for Beginners Tutorial freeCodeCamp
Deep learning using keras in python DigitalSreeni
Deep Learning with Keras Krish Naik

Deep Learning with TensorFlow 2.0 and Keras
第一章 神经网络基础以及TF2初探
第二章 TensorFlow 1.x and 2.x
第三章 回归
第四章 卷积神经网络
第五章 更高级的卷积神经网络
第六章 对抗生成网络
第七章 Word Embedding
第八章 RNN、Seq2Seq以及各种注意力机制
第九章 Auto-encoder 自编码器
第十章 无监督学习（PCA，KMeans，RBM，DBN，VAE）

JAX

JAX The AI Epiphany
Intro to JAX: Accelerating Machine Learning research TensorFlow
JAX Course Weights & Biases
JAX Crash Course - Accelerating Machine Learning code! AssemblyAI
JAX Diffusers Community Sprint Talks: Day 1 HuggingFace
JAX Diffusers Community Sprint Talks: Day 2 HuggingFace
JAX Diffusers Community Sprint Talks: Day 3 HuggingFace
JAX talks HuggingFace

课程

Artificial Intelligence (AI) vs Machine Learning vs Deep Learning vs Data Science codebasics

机器学习算法地图 SIGAI

ML

Python AI Projects NeuralNine
No Black Box Machine Learning Course – Learn Without Libraries freeCodeCamp Radu Mariescu-Istodor
AI 硬體選擇及模型的優化及部署 人工智慧 AI 深度學習軟硬體及框架選擇經驗分享 人工智慧 AppForAI 人工智慧開發工具 Windows 及 Linux 版操作介紹 (淡江大學資管系) 人工智慧 AppForAI-Windows 人工智慧開發工具 s
Machine Learning Explainability Workshop I Stanford Stanford Online
Machine Learning for Everybody – Full Course freeCodeCamp
【机器学习 | 理论与实战】 编程 / Python（文刀出品）B git
Complete Machine Learning and Data Science Courses Nicholas Renotte
MIT 16.412J Cognitive Robotics, Spring 2016 MIT OpenCourseWare
ARTIFICIAL INTELLIGENCE Crack Concepts
跟著大師學科技 Meta School 元學院
Machine Learning freeCodeCamp
人工智能：模型与算法 刘先生 drive 这个好 人工智能：模型与算法 - 浙江大学 刘先生 人工智能：模型与算法 中国大学MOOC-慕课
With The Authors Yannic Kilcher
Clustering and Segmentation Algorithms explained Unfold Data Science
Machine Learning Tutorial Python | Machine Learning For Beginners codebasics
AI Adventures Google Cloud Tech
Machine Learning Algorithm Binod Suman Academy
Neptune Integrations NeptuneAI
【機器學習 2023】(生成式 AI) Hung-yi Lee Autoregressive
【機器學習2022】Hung-yi Lee s git
【機器學習2021】(中文版) Hung-yi Lee
Next Step of Machine Learning (Hung-yi Lee, NTU, 2019) Hung-yi Lee
Advanced Topics in Deep Learning (Hung-yi Lee, NTU) Hung-yi Lee 2018
Machine Learning (Hung-yi Lee, NTU) Hung-yi Lee 2017
Machine Learning From Scratch In Python - Full Course With 12 Algorithms (5 HOURS) Python Engineer
Machine Learning from Scratch - Python Tutorials Python Engineer Patrick Loeber
Cognitive and AI IBM Technology
MIT 6.034 Artificial Intelligence, Fall 2010 MIT OpenCourseWare MIT公开课6.034 人工智能1 (带字幕) 唐逸豪
Machine Learning || Part 1 Geek's Lesson
高级人工智能
邹博　机器学习　曹峰　BiteOfPython　Xuhui Lin　升级版第七期　bt:机器学习理论研究 机器学习课程(全）Min Yuan 2015 小象学院-机器学习班升级版III 砖家王二狗 Deep learning and machine learning HammerResources
Kaggle实战课程　小象　BiteOfPython
End-To-End Data Science with Kaggle | Competition speed run? Nicholas Renotte
Top Kaggle Solution for Fall 2022 Semester Jeff Heaton
七月在线 邹博机器学期算法基础2015年　Min Yuan
大数据的统计基础(完)　掘金　BiteOfPython
课程-人工智能原理 People With_Guitar
北京大学__人工智能原理 知识资源世界(KnowledgeWorld)
中科院高级人工智能全集(35：25：56)
CS188 Artificial Intelligence (Spring 2013) Prof. Pieter Abbeel
中国科学院大学 高级人工智能 沈华伟 博弈(02：50：07)
人工智能导论 浙江工业大学 电子工程世界 共80课时 12小时15分33秒
机器学习-浙江大学2021 刘先生 机器学习-浙江大学（研究生课程） 刘先生 2017 可以搭配李航《统计学习方法》
Tensorflow for Deep Learning Research(Labhesh Patel, )
CS480/680 Intro to Machine Learning - Spring 2019 - University of Waterloo Pascal Poupart
Understanding Machine Learning - Shai Ben David | UWaterloo Rahul Madhavan
CS229: Machine Learning | Summer 2019 (Anand Avati) stanfordonline
Stanford CS229: Machine Learning
Stanford CS229 Machine Learning 2008 吴恩达（Andrew Ng）Stanford homemediaplayer2
机器学习（Machine Learning）吴恩达（Andrew Ng）la fe
吴恩达《2022新版机器学习》课程 NLP从入门到放弃 s
【斯坦福大学】深度学习（全192讲）吴恩达 iMuseums 27:19:55
Andrew Ng’s Machine Learning Specialization 2022 | What is it and is it worth taking? Thu Vu data analytics
EE104: Introduction to Machine Learning stanfordonline
DMQA Lab Open AI/ML Seminar 김성범[ 소장 / 인공지능공학연구소 ]
Meta Learning Shusen Wang
Meta Learning Siraj Raval
机器学习-45-ML-01-Meta Learning(元学习) csdn
Stanford CS221: Artificial Intelligence: Principles and Techniques | Autumn 2019 stanfordonline
Machine Learning for Computational Fluid Dynamics Steve Brunton
CS230: Deep Learning | Autumn 2018 stanfordonline
CS545 - Information and Data Analytics Seminar Series(list, )
Data Analytics Crash Course: Teach Yourself in 30 Days freeCodeCamp
Machine Learning PyB TV NPTEL-NOC IITM Pantech eLearning
机器能像人一样思考吗？人工智能（一）机器学习和神经网络(李永乐老师)
人脸识别啥原理？人工智能（二）卷积神经网络(李永乐老师)
人工智能AI求职与技术(BitTiger官方频道 BitTiger Official Channel)
机器学习真人面试模拟
人工智能、大数据与复杂系统 JK
Machine Learning Coding Tech Daniel Bourke StatQuest with Josh Starmer mathematicalmonk Shital Shah
Machine Learning & Deep Learning Fundamentals deeplizard
Deep Unsupervised Learning -- Berkeley Spring 2020 bilibili
(强推)李宏毅2021春机器学习课程 啥都会一点的研究生 帅帅家的人工智障
Machine Learning Theory Understanding Machine Learning - Shai Ben-David
CS547 - 人机交互研讨会系列 斯坦福在线
AI, ML & Data Science - Training | Projects - Pantech E Learning Pantech eLearning
Artificial Intelligence: Knowledge Representation and Reasoning Artificial Intelligence Z S
July 2019 - Practical Machine Learning with Tensorflow IIT Bombay July 2018
An Introduction to AI - Mausam | IITD - NPTEL Rahul Madhavan
Statistical Learning - Rob and Trevor Hastie | Stanford Rahul Madhavan
Spring 2015: Statistical Machine Learning (10-702/36-702) Ryan T
Spring 2017: Statistical Machine Learning (10-702/36-702) Ryan T
ML - Yaser Abu-Mostafa | Caltech Rahul Madhavan
Machine Learning Course - CS 156 caltech
AI - Patrick Winston | MIT Rahul Madhavan
Computation and the Brain - Christos H. Papadimitriou December 26 - 28 2019 CSAChannel IISc
有趣的机器学习 莫烦Python
机器学习算法基础 覃秉丰 git
机器学习基础配套项目实战课程 覃秉丰 git
机器学习系列课程 Lida Yan
机器学习（Machine Learning）吴恩达（Andrew Ng）la fe
Lecture Collection | Machine Learning 吴恩达（Andrew Ng）Stanford git
机器学习基础：案例研究（华盛顿大学）电子工程世界 共116课时 8小时3分27秒
[2020] 统计机器学习 [Statistical Machine Learning]【生肉】图宾根机器学习 B 33:05:54Statistical Machine Learning — Ulrike von Luxburg, 2020 Tübingen Machine Learning
统计机器学习 电子工程世界 共41课时 1天47分24秒
统计机器学习(张志华) 刘先生
机器学习导论(张志华) 刘先生 电子工程世界 共42课时 1天4小时6分25秒
应用数学基础(张志华)-北京大学 刘先生
人工智能 江西理工 罗会兰 电子工程世界 共40课时 8小时47分20秒
Python机器学习应用 电子工程世界 共27课时 3小时17分52秒
Apprentissage automatique - Université de Sherbrooke Hugo Larochelle
Intelligence Artificielle - Université de Sherbrooke Hugo Larochelle
DeepHack.Turing (2017) DeepPavlov
Theoretical Deep Learning Course DeepPavlov
麦子学院 深度学习基础介绍 机器学习 开发者学堂 课件
麦子学院 深度学习进阶：算法与应用 开发者学堂 Yang Liu
python数据分析与机器学习实战 Yang Liu
机器学习40讲 极客时间
Machine Learning with Python || Machine Learning for Beginners Geek's Lesson
Machine Learning Course for Beginners freeCodeCamp
ML Tutorials AssemblyAI
机器学习　FunInCode
数之道系列 FunInCode
【臺大探索第26期】Future of AI：人工智慧大未來 臺大科學教育發展中心CASE
机器学习入门 黑科技老K git
人人可做的机器学习 跨象乘云
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程式設計 數老的肺炎教室
Machine Learning Elliot Waite
AI And Machine Learning Full Course | AI Tutorial | Machine Learning Tutorial 2022 | Simplilearn 11:29:16
AI And Machine Learning Full Course 2022 | AI Tutorial | Machine Learning Tutorial | Simplilearn 9:59:10
Machine Intelligence Kimia Lab
Machine Learning for beginners Learning AI
Artificial Intelligence Lessons Dr. Daniel Soper
人工智慧實驗教學課程 - 以高中職為例
How I'm Learning AI and Machine Learning macheads101
Machine Learning macheads101
Machine Learning Course - CS 156 caltech
Miscellaneous but useful information about deep learning DigitalSreeni
MACHINE LEARNING CSE & IT Tutorials 4u
Complete Machine Learning playlist Krish Naik
[Tutorialsplanet.NET] Udemy -Artificial Intelligence with Python
Harvard CS50’s Artificial Intelligence with Python – Full University Course freeCodeCamp
[Tutorialsplanet.NET] Udemy - Machine Learning, Deep Learning and Bayesian Learning
机器学习实战---电信客户流失问题 DayDayUP
人工智能核心能力培养 DayDayUP
Machine Learning Luci Date
Stanford AA289 - Robotics and Autonomous Systems Seminar Stanford Online
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人工智能基础-国防科技大学 刘先生

中国人工智能学会 s CAAI w
系列交叉论坛 IT大咖说
系列交叉论坛 第37期 徐宗本 AI的10个重大数理基础问题 pdf zh
演讲实录丨徐宗本院士：如何突破机器学习的先验假设？csdn
AI与数学：融通共进的时代—徐宗本 csdn

Setting Up CUDA, CUDNN, Keras, and TensorFlow on Windows 11 for GPU Deep Learning Jeff Heaton

唐宇迪
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林轩田 Hsuan-Tien Lin(u, )
Machine Learning Foundations (機器學習基石) 机器学习基石 Hsuan-Tien Lin 电子工程世界
Machine Learning Techniques (機器學習技法) 机器学习技法 Hsuan-Tien Lin 电子工程世界

千锋教育
KNN	逻辑回归
线性回归	SVM

概率机器学习 Probabilistic Machine Learning
Probabilistic Machine Learning — Philipp Hennig, 2021 Tübingen Machine Learning [2020] 概率机器学习 [Probabilistic Machine Learning]【生肉】图宾根大学机器学习 B

图机器学习 Machine Learning with Graphs
【图机器学习Machine Learning with Graphs】精译【Stanford 公开课 CS224W (Fall 2021)】(中英双语字幕) B 22:25:02 Stanford CS224W: Machine Learning with Graphs Stanford Online

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DL

2024 Fall 台大資訊 深度學習之應用 NTU CSIE ADL 陳縕儂 Vivian NTU MiuLab
2023 Spring 台大資訊 人工智慧導論 NTU CSIE FAI 陳縕儂 Vivian NTU MiuLab
2022 Fall 台大資工 深度學習之應用 NTU CSIE ADL Vivian NTU MiuLab 2022 Fall 台大資訊 深度學習之應用 NTU CSIE ADL
2022 Spring 台大資工 深度學習之應用 NTU CSIE ADL Vivian NTU MiuLab
2021 Spring 台大資工 深度學習之應用 NTU CSIE ADL Vivian NTU MiuLab
2020 Spring 台大資工 深度學習之應用 NTU CSIE ADL Vivian NTU MiuLab
MIT 6.S192: Deep Learning for Art, Aesthetics, and Creativity Ali Jahanian MIT 6.S192：艺术、美学和创造力的深度学习
Deep Learning & Machine Learning KNOWLEDGE DOCTOR
NVIDIA Deep Learning Course NVIDIA
Deep learning conference Sure
2022 人人有功練：資料科學深度學習 茶米老師教室
Deep Learning Binod Suman Academy
Learn TensorFlow and Deep Learning (beginner friendly code-first introduction) Daniel Bourke
Neural Networks from Scratch in Python（sentdex）
PyTorch for Deep Learning - Full Course / Tutorial freeCodeCamp.org 9:41:39
Ian Goodfellow: Generative Adversarial Networks (GANs) | Lex Fridman Podcast #19
MIT 6.S191: Introduction to Deep Learning Alexander Amini
深度学习原理与实践(天池)
Deep Learning: A Crash Course ACMSIGGRAPH
Deep Networks Are Kernel Machines (Paper Explained) Yannic Kilcher
Bay Area Deep Learning School Shubhabrata Sengupta
深度学习能工作的秘密 (Why Deep Learning Works)：深度神经网络中的隐式自正则化
深度学习理论（斯坦福）爱可可-爱生活
Deep Learning Theories Changkun Ou
Deep Learning Tutorials Changkun Ou
Deep Learning Applications Changkun Ou
Deep Learning NPTEL-NOC IITM 迷途小书童
Theoretical Deep Learning Nilotpal Sinha Shital Shah
Deep Learning for Computer Architects CoffeeBeforeArch
DeepLearning - Mitesh Khapra, SKS Iyengar || IIT Ropar and Madras - NPTEL Rahul Madhavan
Deep Learning - Andrew Ng Kian Katanforoosh | Stanford - OnlineHub Rahul Madhavan
Deep Learning - Ali Ghodsi | STAT 946 - U.Waterloo Rahul Madhavan
Deep Learning Course by Sargur N. Srihari CSAChannel IISc
Deep Learning by Sargur N. Srihari CSAChannel IISc
Deep Learning Course NVIDIA Developer
Neural networks class - Université de Sherbrooke Hugo Larochelle
[Coursera] Neural Networks for Machine Learning — Geoffrey Hinton Colin Reckons
Deep Learning Crash Course for Beginners　freeCodeCamp
Practical Deep Learning for Coders - Full Course from fast.ai and Jeremy Howard freeCodeCamp
Neural Networks from Scratch with Python and Opencv Pysource
CS294-158 Deep Unsupervised Learning Dhanabhon Subha-asavabhokhin
How Deep Neural Networks Work - Full Course for Beginners freeCodeCamp
人工智能与机器学习 做大饼馅儿的韭菜
Intuitive Deep Learning 深度碎片
Deep Learning: CS 182 Spring 2021 RAIL
NIPS 2016 Deep Learning for Action and Interaction Workshop RAIL
Ilya Sutskever: Deep Learning | Lex Fridman Podcast #94 Lex Fridman
GPT-4 Creator Ilya Sutskever Eye on AI
Ilya Sutskever (OpenAI Chief Scientist) - Building AGI, Alignment, Spies, Microsoft, & Enlightenment Dwarkesh Patel
Sam Altman回归！聊聊“叛变者”的恐惧与信念：OpenAI技术灵魂人物Ilya Sutskever 硅谷101
The Robot Brains Podcast u Ilya Sutskever
伊利亚·苏茨克沃 苏神 OpenAI的联合创始人和首席科学家 谷歌大脑 人工智能科学家 AlphaGo论文作者之一 OpenAI到底是一家怎样的公司？ 量子位 Inside OpenAI [Entire Talk] Stanford eCorner
OpenAI成长史：顶级资本与科技大佬的理想主义，冲突，抉择与权力斗争；马斯克、奥特曼、纳德拉与比尔·盖茨等人的背后故事【深度】 硅谷101 Greg Brockman OpenAI CEO CTO
Deep Learning Basics: Introduction and Overview Lex Fridman
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LEX Fridman MIT Lectures AR
MIT 6.S094 Lily Z.
Complete Deep Learning Krish Naik
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Machine Learning & Neural Networks without Libraries – No Black Box Course freeCodeCamp

动手学深度学习

动手学深度学习	课程安排
Apache MXNet/Gluon 中文频道	跟李沐学AI(B, )
ApacheMXNet(B, u, )
s, git, 论坛, book(v1, v2, )	《动手学深度学习》 第二版预览版
v2视频(B, ), v2视频(B, ),	深度学习论文精读 git
【李沐】动手学深度学习-pytorch 2021版 Math4AI 数据丢失
Mu Li u	跟李沐学AI u

DeepLearningAI

Deep Learning Specialization
(Course 1) Neural Networks and Deep Learning
(Course 2) Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
(Course 3) Structuring Machine Learning Projects
(Course 4) Convolutional Neural Networks
(Course 5) Sequence Models
Heroes of Deep Learning
Heroes of NLP

Data Science

数据科学

Python And Data Science Full Course | Data Science With Python Full Course In 12 Hours | Simplilearn
Build 12 Data Science Apps with Python and Streamlit - Full Course(freeCodeCamp)
数据挖掘 Dayin HE
分布式项目实战 Online learning网络课堂
Data Science - Learn to code for beginners deeplizard
Intro to Data Science Steve Brunton
Python for Data Science NPTEL-NOC IITM
Tools in Scientific Computing IIT Kharagpur July 2018
MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016 MIT OpenCourseWare
Python for Data Science - Course for Beginners (Learn Python, Pandas, NumPy, Matplotlib) freeCodeCamp
Data Analysis with Python - Full Course for Beginners (Numpy, Pandas, Matplotlib, Seaborn) freeCodeCamp 4:22:12
Data Analysis Tutorial for Beginners Geek's Lesson
Data Analysis with Python for Excel Users - Full Course freeCodeCamp
Build 12 Data Science Apps with Python and Streamlit - Full Course freeCodeCamp
Data Analysis with Python Course - Numpy, Pandas, Data Visualization freeCodeCamp
Intro to Data Science - Crash Course for Beginners freeCodeCamp
Solving real world data science tasks with Python Pandas! Keith Galli
Keynote Jake VanderPlas PyData
Reproducible Data Analysis in Jupyter Jake Vanderplas
Data Mining資料採礦課程 謝邦昌
Data Science 101 Data Professor
Learn Data Science Tutorial - Full Course for Beginners freeCodeCamp
Full Data Science Course Learn Python with Rune
Data Science freeCodeCamp
Data Science and Machine Learning with Python and R Krish Naik
Polars: The Next Big Python Data Science Library... written in RUST? Rob Mulla
Data Science Job Interview – Full Mock Interview freeCodeCamp
python 数据分析（中国国家精品课程） 华人开放式课程MOOC
Data Science/ML Projects JCharisTech
10x Your Data Science With Polars Machine Learning with Phil

数据清理

The Ultimate Guide to Data Cleaning towardsdatascience

斯坦福CS329P：实用机器学习 Mu Li 主页

算法

奥卡姆剃刀原理(ccam's razor) 严伯钧 v8:33 entities should not be multi-plied beyond necessity

LightGBM(site, paper, github, wiki, pypi)

Dijkstra's Algorithm(v, )

XGBoost 中文文档(书栈, )
XGBoost StatQuest with Josh Starmer
算法：Xgboost提升算法 开发者学堂
XGBoost与LightGBM 数据科学家常用工具大PK——性能与结构 Data Application Lab
Time Series Forecasting with XGBoost - Use python and machine learning to predict energy consumption Medallion Data Science

极客学院机器学习训练营

机器学习环境配置手册 github 0期课程大纲

scikit-learn (sklearn)

scikit-learn.org
機器學習：使用Python (书栈, )
scikit-learn (sklearn) 0.21.3 官方文档中文版 (书栈, )
Scikit-Learn Python Tutorial | Machine Learning with Scikit-learn ProgrammingKnowledge
Jake VanderPlas: Machine Learning with Scikit Learn PyData
Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc) Keith Galli
Learn Scikit Learn Normalized Nerd
Professional Preprocessing with Pipelines in Python NeuralNine
Precision & Recall in Machine Learning Explained NeuralNine
机器学习Sklearn全套教程（程序员必备）千锋教育 drive
Traditional Machine Learning in Python DigitalSreeni
Scikit-Learn Tutorial | Machine Learning With Scikit-Learn | Sklearn | Python Tutorial | Simplilearn
Scikit-Learn Course - Machine Learning in Python Tutorial freeCodeCamp
Scikit-learn Crash Course - Machine Learning Library for Python freeCodeCamp
Learning Scikit-Learn Google Cloud Tech
Introduction to scikit-learn Lander Analytics
Introduction to Python in Google Colab and Introduction to Sci Kit Learn Veronica Red
Python in Data Science for Intermediate learndataa
Understanding Pipeline in Machine Learning with Scikit-learn (sklearn pipeline) Dr. Data Science
Machine learning in Python with scikit-learn Data School
Scikit-Learn Model Pipeline Tutorial Greg Hogg
Using Scikit-Learn Pipelines for Data Preprocessing with Python Nicholas Renotte

预测

08预测 课堂商业

Stock Price Prediction & Forecasting with LSTM Neural Networks in Python Greg Hogg colab	Rain Prediction | Building Machine Learning Model for Rain Prediction using Kaggle Dataset SPOTLESS TECH

Kaggle Titanic Survival Prediction
Titanic Survival Prediction in Python - Machine Learning Project NeuralNine	Desafio Kaggle: Titanic - Preparando os dados - Parte 1 DevVerso [BR]	Logistic Regression with Python | Titanic Data | Your First Kaggle Project | Analytics Summit
Kaggle Titanic Survival Prediction Competition Part 1/2 - Exploratory Data Analysis Jason Chong

分类

CART - Classification And Regression Trees StatQuest with Josh Starmer
算法：决策树 开发者学堂
Decision Tree Classification Clearly Explained! Normalized Nerd

线性回归 & 线性模型 Linear Regression and Linear Models

Linear Regression and Linear Models StatQuest with Josh Starmer
【千锋大数据】机器学习之线性回归教程（6集）千锋教育

多元线性回归, multi variate Linear Regression

18 多元线性回归 南京大学周志华 Darics

逻辑回归 Logistic Regression

Logistic Regression StatQuest with Josh Starmer
【千锋大数据】机器学习之逻辑回归教程（6集）千锋教育
線性機率模型 (LPM) 與邏輯斯迴歸 (Logistic Regression) 張翔老師
【Stata小课堂】第24讲：有序多分类Logistic回归(Ordinal Logistic Regression) Mingyu Zhang
Big Data Analysis - Regression 李政軒
Tutorial 35- Logistic Regression Indepth Intuition- Part 1| Data Science Krish Naik
08逻辑回归算法 课时46逻辑回归算法原理推导 互联网开发教程 tyd
Logistic Regression - Is it Linear Regression? CodeEmporium

决策树

Decision Tree Classification Algorithm in Telugu CSE & IT Tutorials 4u
剪支 pruning

随机森林 Random Forests

What is Random Forest? IBM Technology
Random Forests StatQuest with Josh Starmer
算法：随机森林与集成算法 开发者学堂
一套完整的基于随机森林的机器学习流程（特征选择、交叉验证、模型评估））生信宝典
Random Forest Algorithm Clearly Explained! Normalized Nerd
How Do Random Forests Work & What is Ensemble Learning NeuralNine

MLP

MLP-Mixer: An all-MLP Architecture for Vision arxiv towardsdatascience git git medium reddit reddit arxiv-vanity programmersought
MLP-Mixer: An all-MLP Architecture for Vision (Machine Learning Research Paper Explained) Yannic Kilcher
MLP Mixer Is All You Need? towardsdatascience morioh
MLP-Mixer：一个比ViT更简洁的纯MLP架构 知乎 陀飞轮
MLP-Mixer: MLP is all you need... again? ... mchromiak
Unofficial implementation of MLP-Mixer: An all-MLP Architecture for Vision pythonrepo
Prediction using Artificial Neural Network (MLP) - Predict Car Price Roy Jafari
What are MLPs (Multilayer Perceptrons)? IBM Technology
Multilayer Perceptrons - Ep.6 (Deep Learning Fundamentals) Power H
Perceptron Algorithm with Code Example - ML for beginners! Python Simplified

KAN

使用KAN网络，更少参数更高准确率，更好的可解释性 替代传统MLP！Find Interesting AI

聚类 Clustering 集簇

Theory of Clustering Understanding Machine Learning - Shai Ben-David
人工智能案例：聚类实践 开发者学堂
ML: Clustering Data analysis with Python - Spring 2020 colab git
Numpy: Kmeans Clustering from Scratch GNT Learning
K-means & Image Segmentation - Computerphile
K-Means Clustering From Scratch in Python (Mathematical) NeuralNine
周志华 Darics
聚类的"好坏"不存在绝对的标准
寻找标准是关键
常见的聚类方法 原型聚类 亦称"基于原型的聚类"(prototype-based clustering) 假设:聚类结构能够通过一组原型刻画 过程:先对原型初始化, 然后对原型进行迭代更新求解 代表:k均值聚类, 学习向量量化(LVQ), 高斯混合聚类 密度聚类 亦称"基于密度的聚类"(density-based clustering) 假设:聚类结构能够通过样本分布的紧密程度确定 过程:从样本密度的角度来考察样本之间的可连续性, 并基于可连接样本不断扩展聚类蔟 代表:DBSCAN, OPTICS, DENCLUDE 层次聚类(hierarchical clustering) 假设:能够产生不同粒度的聚类结果 过程:在不同层次对数据集进行划分, 从而形成树形的聚类结构 代表:AGNES(自低向上), DIANA(自顶向下)

回归 Regression

算法：线性回归算法 开发者学堂
案例实战 信用卡欺诈检测 开发者学堂
线性回归　Ouyang Ruofei　git
How to implement Linear Regression from scratch with Python AssemblyAI
高斯过程　v
Lasso Regression Udacity
Lecture 21: LASSO Anders Munk-Nielsen
10b Machine Learning: LASSO Regression GeostatsGuy Lectures
Polynomial Regression in Python NeuralNine
Poisson regression with tidymodels for package vignette counts Julia Silge
Regression Analysis | Full Course DATAtab
How to do Multiple Linear Regression in Python| Jupyter Notebook|Sklearn Megha Narang
Multivariable Linear Regression using Gradient Descent Algorithm in Python,Step by Step from scratch PAUL ACADEMY
Multiple Linear Regression using python and sklearn Krish Naik
Statistics PL15 - Multiple Linear Regression Brandon Foltz
Linear Regression From Scratch in Python (Mathematical) NeuralNine
简单线性回归简介（simple linear regression ）Python统计66——Python程序设计系列169 Andrew 程序设计
11 1 简单线性回归的统计描述 11 医学统计学-郝元涛（中山大学）
Bayesian Linear Regression: Simple Linear Regression Review Lazy Programmer
Bayesian Linear Regression: Distribution of Parameter Estimate Lazy Programmer
Machine Learning Foundations Course – Regression Analysis freeCodeCamp
Interpreting Linear Regression Results Sergio Garcia, PhD
线性回归 Darics 南京大学周志华

KNN

【千锋大数据】3天快速入门机器学习（9集） 千锋教育

How kNN algorithm works Thales Sehn Körting

How to implement KNN from scratch with Python AssemblyAI

Heart Disease Predictor Model Using KNN Classifier |Machine Learning| Python | Project For Beginners AI Sciences

Implementation of KNN Algorithm using Iris Dataset in Jupyter Notebook | JAcademy

KNN Algorithm In Machine Learning | KNN Algorithm Using Python | K Nearest Neighbor | Simplilearn	KNN (K-Nearest Neighbor) Algorithm in Telugu CSE & IT Tutorials 4u	K - Nearest Neighbors - KNN Fun and Easy Machine Learning Augmented Startups
Predicting CS:GO Round Winner with Machine Learning NeuralNine	K-Nearest Neighbors Classification From Scratch in Python (Mathematical) NeuralNine	K-Nearest Neighbors Algorithm From Scratch In Python The Teen Innovator

时间序列 Time Series

算法：时间序列AIRMA模型 开发者学堂
案例：时间序列预测任务 开发者学堂
时间序列分析：用数据做预测（第595期）Data Application Lab
数据科学读书会 Book 15 – 《Hands-on Time Series Analysis with Python》 时间序列分析 第一讲 Data Application Lab
数据科学读书会 Book 15 - 时间序列分析 单变量时间序列v
Structured Learning 4: Sequence Labeling Hung-yi Lee
Time Series Prediction Siraj Raval
Time Series Analysis：Data Scientist是如何做时间序列分析的？（第566期） Data Application Lab
Time Series Analysis (Forecasting, Mining, Transformation, Clustering, Classification) + Python code Hadi Fanaee git
Data Mining資料採礦課程 謝邦昌
Time Series Analysis ritvikmath
02417 Time Series Analysis Lasse Engbo Christiansen 2018
02417 Time Series Analysis, Fall 2017 Lasse Engbo Christiansen
02417 Time series analysis, Fall 2016 Lasse Engbo Christiansen
Time Series Theory Analytics University
Time Series Forecasting Theory
Multivariate Time Series Forecasting with LSTM using PyTorch and PyTorch Lightning (ML Tutorial) Venelin Valkov
Multivariate Time Series Forecasting Using LSTM, GRU & 1d CNNs Greg Hogg
1D Convolutional Neural Networks for Time Series Modeling - Nathan Janos, Jeff Roach PyData
Convolutional neural networks with dynamic convolution for time series classification Krisztian Buza
Webinar: Time-series Forecasting With Model Types: ARIMAX, FBProphet, LSTM NeptuneAI
161 - An introduction to time series forecasting - Part 1 DigitalSreeni
162 - An introduction to time series forecasting - Part 2 Exploring data using python DigitalSreeni
163 - An introduction to time series forecasting - Part 3 Using ARIMA in python DigitalSreeni
166 - An introduction to time series forecasting - Part 5 Using LSTM DigitalSreeni
181 - Multivariate time series forecasting using LSTM DigitalSreeni
Time Series Analysis (ARIMA) using Python Tathya Bislesan
Time Series Analysis For Rainfall Prediction Using LSTM Model - Explained For Beginners AI Sciences
Time Series Forecasting with XGBoost - Use python and machine learning to predict energy consumption Medallion Data Science
Time Series Analysis with FB Prophet JCharisTech

支持向量机 SVM

Support Vector Machines StatQuest with Josh Starmer
算法：线性支持向量机 开发者学堂
【千锋大数据】机器学习之SVM教程（9集） 千锋教育
Understanding SVM ,its Type ,Applications and How to use with Python engineerknow
Support Vector Machine Algorithm in Telugu CSE & IT Tutorials 4u
Support Vector Machine - How Support Vector Machine Works | SVM In Machine Learning | Simplilearn
Support Vector Machine - SVM - Classification Implementation for Beginners (using python) - Detailed Cloud and ML Online
Support Vector Machine (SVM) Basic Intuition- Part 1| Machine Learning Krish Naik

Kernel Method

Kernel Method 李政軒

神经网络, Neural Networks, NN

Neural Networks StatQuest with Josh Starmer
Gradient Boost StatQuest with Josh Starmer
Batch Normalization - EXPLAINED! CodeEmporium
Optimizers - EXPLAINED! CodeEmporium
Liquid Neural Networks MITCBMM
Neural Networks from Scratch with Python and Opencv Pysource
How Deep Neural Networks Work - Full Course for Beginners freeCodeCamp
深度神经网络的工作原理 Brandon Rohrer
Stanford Seminar - Incorporating Sample Efficient Monitoring into Learned Autonomy Stanford Online
The Mathematics of Neural Networks Art of the Problem
Illustrated Guide to Deep Learning The A.I. Hacker - Michael Phi
How are memories stored in neural networks? | The Hopfield Network #SoME2 Layerwise Lectures
Hopfield Networks is All You Need (Paper Explained) Yannic Kilcher
Talk | FAIR研究科学家刘壮：高效和可扩展的视觉神经网络架构 将门-TechBeat技术社区
深度学习基础介绍 机器学习19 神经网络NN算法 开发者学堂 git
Neural Networks are Decision Trees (w/ Alexander Mattick) Yannic Kilcher
Visualizing and Understanding Deep Neural Networks by Matt Zeiler Data Council
GLOM: How to represent part-whole hierarchies in a neural network (Geoff Hinton's Paper Explained) Yannic Kilcher
[DMQA Open seminar] Backbone Network in Deep learning Sejin Sim
How to Create a Neural Network (and Train it to Identify Doodles) Sebastian Lague
Neural Network Primer Luci Date
10 Tips for Improving the Accuracy of your Machine Learning Models Jeff Heaton
Neural Networks: Zero to Hero Andrej Karpathy OpenAI 核心成员, 特斯拉自动驾驶
你能不能训练一个GPT类大型语言模型？基地 安德鲁·卡帕西（Andrej Karpathy）
Neural Network from Scratch | Mathematics & Python Code The Independent Code
Gradient Descent From Scratch in Python - Visual Explanation NeuralNine
Deriving the Ultimate Neural Network Architecture from Scratch #SoME3 Algorithmic Simplicity

万能近似定理（universal approximation theorrm）
神经网络的万能逼近定理已经发展到什么地步了？ zh	Why Neural Networks can learn almost anything Emergent Garden	s

RBF Networks

RBF Networks macheads101
Lecture 16 - Radial Basis Functions caltech
Mod-01 Lec-27 RBF Neural Network nptelhrd
Mod-01 Lec-28 RBF Neural Network (Contd.) nptelhrd

参数追踪 参数可视化

Visualize Neural Networks

4 Ways To Visualize Neural Networks in Python JCharisTech	Track your machine learning experiments locally, with W&B Local - Chris Van Pelt Weights & Biases search

自动微分 自动求导

自动微分 ZOMI	MindSpore初学教程 ZOMI

计算图

计算图 ZOMI AI框架之计算图
"图计算"和"计算图"是不同的概念，尽管它们之间有一些关联。 "计算图"通常指的是一种表示计算过程的图形结构，其中节点表示计算操作，边缘表示数据流。它通常被用于深度学习中，以表示神经网络的计算过程。在计算图中，每个节点执行特定的数学运算，并将结果传递给后续节点。这种图形表示方式有助于优化计算和自动求导。 "图计算"是一种计算模型，它使用图形结构来表示和处理数据。它的基本思想是将数据存储为图形结构，然后使用图形算法来处理数据。图计算可以应用于许多领域，例如社交网络分析、推荐系统和生物信息学。 因此，尽管它们之间有一些相似之处，但"图计算"和"计算图"是不同的概念。"计算图"是一种表示计算过程的图形结构，而"图计算"是一种使用图形结构来表示和处理数据的计算模型。

RNN Recurrent Neural Networks

Recurrent Neural Networks - EXPLAINED! CodeEmporium

LSTM

LSTM Networks - EXPLAINED! CodeEmporium

蒙特卡洛 Monte Carlo

蒙特卡洛树搜索 Monte Carlo Tree Search (MCTS)
6. Monte Carlo Simulation MIT OpenCourseWare MIT 6.0002
蒙特卡洛树搜索基础（Monte Carlo Tree Search)　技术喵
【讀論文】蒙地卡羅 詳細過程 | Monte Carlo Tree Search| 遊戲樹 K66
2 3 蒙特卡洛树搜索 中国大学MOOC-慕课 s
Monte Carlo Tree Search 1 2 Udacity
Monte Carlo Tree Search (MCTS) Tutorial Fullstack Academy
蒙特卡洛 Monte Carlo Shusen Wang
Monte Carlo Inference 徐亦达
数学_蒙地卡罗法和Buffon needle简介 PengTitus
【数之道 21】随机抽样、蒙特卡洛模拟与逆转换方法 FunInCode 将简单的均匀分布抽样转化为复杂分布抽样的方法: 逆转换方法 Inverse Transform Sampling
【数之道 22】巧妙使用"接受-拒绝"方法，玩转复杂分布抽样 FunInCode 接受拒绝抽样 Acceptance Rejection Sampling
Monte Carlo simulation for Conditional VaR (Excel) NEDL
MATLAB小课堂——如何使用蒙特卡洛模拟进行预测？ MATLAB
Advanced 4. Monte Carlo Tree Search MIT OpenCourseWare
Tongkui Yu u
AI如何下棋？直观了解蒙特卡洛树搜索MCTS!!! 图灵鸡科技俱乐部

马尔可夫 马尔科夫 Markov

OR 10-2 馬可夫性質與馬可夫鏈(李維OR) 小卒數理學堂
徐亦达机器学习课程 Markov Chain Monte Carlo (part 1) (part 2)(3)(4)徐亦达
Intro to Reinforcement Learning 强化学习纲要 第二课 马尔科夫决策过程 上 下 Bolei Zhou
15讲01 隐马尔科夫模型的基本概念　MM li
隐马尔科夫模型　Ouyang Ruofei
程序数学之随机过程 Jomy King
A friendly introduction to Bayes Theorem and Hidden Markov Models Serrano.Academy Luis Serrano
馬可夫不等式 CUSTCourses
Lecture 8: Markov Decision Processes (MDPs) CS188Spring2013
Finite Math: Introduction to Markov Chains Brandon Foltz
馬可夫鏈基礎1 Chen Kiwii 馬可夫鏈進階1 Chen Kiwii
Hidden Markov Model 徐亦达
程序数学之随机过程 Jomy King csdn
【数之道 20】5分钟理解'马尔可夫链'的遍历性与唯一稳态 Markov Chain's Ergodicity and Stationary Distribution FunInCode
Lecture 7: Markov Decision Processes - Value Iteration | Stanford CS221: AI (Autumn 2019) stanfordonline
Markov Decision Processes (MDPs) - Structuring a Reinforcement Learning Problem deeplizard
Stanford教授Daphne Koller 概率图模型 — 终极入门 第三讲 马尔可夫网络 (Markov Networks) pdf
Markov Chains Clearly Explained! Normalized Nerd
用Python介绍马尔可夫链！ Adrian Dolinay
[Tutorialsplanet.NET] Udemy - Unsupervised Machine Learning Hidden Markov Models in Python

MCMC, Markov Chain Monte Carlo

基于采样的马尔可夫链蒙特卡罗(Markov Chain Monte Carlo，简称MCMC)方法

[硬核公式推导系列] 蒙特卡洛模拟与MCMC 技术喵　git Box-Muller算法？ 接受拒绝抽样 Acceptance Rejection Sampling metropolis Hastings Gibbs Sampling
为什么要使用MCMC方法？zh
一文读懂贝叶斯推理问题：MCMC方法和变分推断 zh
17讲02 近似推断法：MCMC和变分推断 MM li
随机数算法, Sobol列 v 25:07

维特比算法 The Viterbi Algorithm

维特比算法 The Viterbi Algorithm

基于维特比算法的文本分词 (Greedy Academy) 贪心学院 Greedy AI

任务024：分词 维特比算法 William 砖家王二狗

Viterbi Algorithm Keith Chugg

汉语自然语言处理-维特比算法与NER-命名实体识别-viterbi algorithm-HMM-CRF-概率图模型-动态规划 Shurui Zhang B

Decoding Convolutional Codes: The Viterbi Algorithm Explained Iain Explains Signals, Systems, and Digital Comms

The Viterbi Algorithm : Natural Language Processing ritvikmath

(ML 14.11) Viterbi algorithm (part 1) mathematicalmonk

人工智慧 -- 機率統計法 (HMM 隱碼可夫模型與 viterbi 算法）陳鍾誠

STAT115 Chapter 14.6 Viterbi Algorithm Xiaole Shirley Liu

Digital Communications: Viterbi Algorithm UConn HKN

Hidden Markov Models 11: the Viterbi algorithm djp3

条件随机场 Conditional Random Fields

条件随机场 Conditional Random Fields

第8课 条件随机场与应用 七月在线 4399 gala

16讲02 条件随机场的定义与形式 MM li

任务260： CRF介绍 砖家王二狗

任务390： 利用CRF模型做命名实体识别 01 砖家王二狗

Conditional Random Fields - Stanford University (By Daphne Koller) Machine Learning TV

Conditional Random Fields Natalie Parde

Lec 9: Conditional Random Fields (1/3) (2/3) (3/3) LUCY Yin

因子分解机Factorization Machine, FM

直观讲解因子分解机Factorization Machine 技术喵
Steffen Rendle. Factorization machines pdf 2010 IEEE
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction arxiv 2017
xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems arxiv 2018
Building a Social Network Content Recommendation Service Using Factorisation Machines - Conor Duke Python Ireland

最大熵

Maximum Entropy Methods Tutorial Complexity Explorer
Entropy (for data science) Clearly Explained!!! StatQuest with Josh Starmer

集成学习 Ensemble Learning

三个丑皮匠 顶个诸葛亮
集成学习 Ouyang Ruofei
GradientBoost Ouyang Ruofei
[Tutorialsplanet.NET] Udemy - Ensemble Machine Learning in Python Random Forest, AdaBoost
Ensembles Luci Date
集成学习 南京大学周志华教授亲讲 Darics
序列化方法 AdaBoost(Boosting家族) GradientBoost(XGBoost*) LPBoost 异质配准Alignment
并行化方法 Bagging Random Forest* Random Subspace
E = E' - A', diversity is A'
圣杯 "What is diversity" remains the holy grail problem of ensemble learning
How Do Random Forests Work & What is Ensemble Learning NeuralNine

多任务学习 Multi-task learning

Community Talks on Day 2 | PyTorch Developer Day 2021 PyTorch
Stanford CS330: Deep Multi-Task and Meta Learning stanfordonline
Stanford CS330: Deep Multi-Task & Meta Learning I Autumn 2021I Professor Chelsea Finn Stanford Online
Stanford CS330: Deep Multi-Task and Meta Learning I Autumn 2022 Stanford Online

AutoML 机器学习自动化调参

机器学习自动化调参 Ouyang Ruofei
神经网络结构搜索 Neural Architecture Search Shusen Wang
神经网络（十二） 自动神经网络（AutoML）与网络架构搜索（NAS） 技术喵
Hyperparameter Tuning in Python with GridSearchCV NeuralNine
ROC Optimal Threshold ► Data Science Exercises #22 Gleb Mikhaylov
AutoML with Auto-Keras (14.1) Jeff Heaton
169 - Deep Learning made easy with AutoKeras DigitalSreeni
171 - AutoKeras for image classification using cifar10 data set DigitalSreeni
Automated Deep Learning with AutoKeras Data Heroes
I tried building a AUTO MACHINE LEARNING Web App 15 Minutes Nicholas Renotte
Neural Architecture Search Connor Shorten
Create Simple AutoML System from Scratch Jeff Heaton

机器学习可解释性

CVPR'20 Interpretable Machine Learning Tutorial Bolei Zhou
Talk | 微软亚洲研究院王希廷：基于逻辑规则推理的深度自可解释模型 将门-TechBeat技术社区

对比学习 contrastive learning

对比学习（Contrastive Learning）是一种无监督学习方法，旨在通过将相似的样本进行比较来学习有用的表示。在对比学习中，算法试图将来自同一类别的样本分组在一起，并将来自不同类别的样本分开。这可以通过比较两个或多个样本的表示来实现，例如将它们映射到一个低维向量空间中。 对比学习通常用于解决许多计算机视觉问题，例如图像分类、目标检测和语义分割。在这些问题中，通常需要大量的有标签数据来训练模型，而对比学习则提供了一种可以使用无标签数据进行训练的替代方案。 在最近的研究中，对比学习已经被证明在许多任务上具有出色的性能，例如自然语言处理和推荐系统。由于其可扩展性和适应性，对比学习已经成为了当前深度学习领域的一个热门话题。
SimCLR sota
Talk | 剑桥大学在读博士生苏熠暄：对比搜索（Contrastive Search）—当前最优的文本生成算法 将门-TechBeat技术社区
MoCo 论文逐段精读【论文精读】 Mu Li 视觉 无监督表示学习 动量对比学习 Momentum Contrast(MoCo)
对比学习论文综述【论文精读】 Mu Li

少样本学习 Few-Shot Learning Zero Shot One Shot

Meta Learning Shusen Wang
Meta Learning Siraj Raval
Meta-Learning and One-Shot Learning macheads101
Model Agnostic Meta Learning Siavash Khodadadeh
Learning to learn: An Introduction to Meta Learning Machine Learning TV
Meta learning by Hugo yet Shell
Ilya Sutskever: OpenAI Meta-Learning and Self-Play | MIT Artificial General Intelligence (AGI) Lex Fridman
各種奇葩的元學習 (Meta Learning) 用法 Hung-yi Lee
【機器學習2021】元學習 Meta Learning (一) - 元學習跟機器學習一樣也是三個步驟 Hung-yi Lee
【機器學習2021】元學習 Meta Learning (二) - 萬物皆可 Meta Hung-yi Lee
Few Shot Learning - EXPLAINED! CodeEmporium
Few-shot learning in production HuggingFace
OpenAI's CLIP for Zero Shot Image Classification James Briggs
Fast Zero Shot Object Detection with OpenAI CLIP James Briggs
Stanford CS330: Deep Multi-Task and Meta Learning I Autumn 2022 Stanford Online
Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning The Global NLP Lab

注意力

神经网络（四） 注意力机制 技术喵
RNN模型与NLP应用 Shusen Wang
Transformer模型 Shusen Wang
【機器學習 2022】各式各樣神奇的自注意力機制 (Self-attention) 變型 Hung-yi Lee
Attention in Neural Networks CodeEmporium

损失函数

机器学习常用损失函数小结 王桂波

机器学习如何选择回归损失函数的？ csdn

神经网络的损失函数为什么是非凸的? zh

联邦学习 Federated Learning

Chaoyang He u no瞎哔哔 B
联邦学习：技术角度的讲解（中文）Introduction to Federated Learning Shusen Wang
杨强 | 用户隐私，数据孤岛和联邦学习 清华大学智能产业研究院
刘洋丨联邦学习的技术挑战和应用展望 清华大学智能产业研究院
分布式机器学习 Shusen Wang
FedML联邦机器学习开源框架视频教程全集 Chaoyang He
[Tutorial] FedML: a research library for federated machine learning Chaoyang He
90秒入门联邦学习 Federated learning 微软智汇AI
什么是联邦学习（Federated Learning）？【知多少】 KnowingAI知智
详解联邦学习Federated Learning - 知乎 机器朗读
联邦学习与个性化联邦学习 感知互联与数据智能

AB测试 A/B testing

5 concepts of A/B testing you should know as a Data Scientist CodeEmporium
How to run A/B Tests as a Data Scientist! CodeEmporium
AB Testing概览 课代表立正
A/B Testing：轻松Pass二轮面试！AB 测试具体步骤及参数详解，附具体案例演示及结论分析 Data Application Lab
A/B Testing面试干货： 一个你以为你会但总挡住你拿offer的必学知识点 - A/B测试（第427期） Data Application Lab
商业分析师AB测试设计实战技巧，大厂Business Analyst为你实例解析AB Testing（第520期）Data Application Lab
AB test calculator (pet project) | Gleb Builds #2 Gleb Mikhaylov

CTC

Phoneme Detection with CNN-RNN-CTC Loss Function - Machine Learning Ali Yektaie
CTC for Offline Handwriting Recognition Oliver Nina
F18 Recitation 8: Connectionist Temporal Classification (CTC) u
S18 Lecture 14: Connectionist Temporal Classification (CTC) u

因果推断 Causal inference

什么是因果推断Causal inference？为什么数据科学家要知道这个？（第612期） Data Application Lab
数据科学读书会 Book 17 – 因果推断 因果效应(Causal Effect) Data Application Lab
数据科学读书会 Book 17 - 因果推断-因果推断的公式和模型 Data Application Lab
探索因果规律之因果推断基础（ft. The Book of Why by Judea Pearl) 技术喵
因果效应学习基础 技术喵
《为什么》关于因果关系的新科学 每天听书 Wise AudioBooks

蚁群算法

【数之道 04】解决最优路径问题的妙招-蚁群ACO算法 FunInCode

Autoencoder

What is an Autoencoder? | Two Minute Papers #86 Two Minute Papers	Simple Explanation of AutoEncoders WelcomeAIOverlords	Autoencoders - EXPLAINED CodeEmporium
What are Autoencoders? IBM Technology	Autoencoders - Ep. 10 (Deep Learning SIMPLIFIED) DeepLearning.TV	85a - What are Autoencoders and what are they used for? DigitalSreeni
	Understanding and Applying Autoencoders in Python! Spencer Pao	85b - An introduction to autoencoders - in Python DigitalSreeni
Autoencoder Dimensionality Reduction Python TensorFlow / Keras #CodeItQuick Greg Hogg	Autoencoders Explained Easily Valerio Velardo - The Sound of AI	Autoencoders Made Simple! Professor Ryan

VAE Variational Autoencoder

Ali Ghodsi, Lec : Deep Learning, Variational Autoencoder, Oct 12 2017 [Lect 6.2] Data Science Courses
Variational Autoencoders Arxiv Insights
Variational Autoencoders - EXPLAINED! CodeEmporium
Autoencoder Explained Siraj Raval
178 - An introduction to variational autoencoders (VAE) DigitalSreeni
179 - Variational autoencoders using keras on MNIST data DigitalSreeni
VAE-GAN Explained! Connor Shorten
What are Generative Models? | VAE & GAN | Intro to AI Zhuoyue Lyu
Build a Stable Diffusion VAE From Scratch using Pytorch freeCodeCamp

变分推断 Variational Inference

通常在研究贝叶斯模型中，需要去求解一个后验概率(Posterior)分布，但是由于求解过程的复杂性，因此很难根据贝叶斯理论求得后验概率分布的公式精确解，所以一种方法是用一个近似解来替代精确解，并使得近似解和精确解的差别不会特别大。一般求解近似解的方法有两种：第一种是基于随机采样的方法，比如用蒙特卡洛采样法去近似求解一个后验概率分布；第二种就是变分贝叶斯推断法。变分贝叶斯法是一类用于贝叶斯估计和机器学习领域中近似计算复杂积分的技术。它关注的是如何去求解一个近似后验概率分布。s
Variational Inference: Foundations and Modern Methods (NIPS 2016 tutorial) Steven Van Vaerenbergh
如何简单易懂地理解变分推断(variational inference)？ zh

变分自编码

变分推断与变分自编码器 s

EM算法

The EM Algorithm Peter Green

其他

人工智慧在臺灣：產業轉型的契機與挑戰｜陳昇瑋研究員 中央研究院Academia Sinica
BUILD and SELL your own A.I Model! $500 - $10,000/month (super simple!) Code with Ania Kubów
Machine Learning Projects You NEVER Knew Existed Nicholas Renotte

数据收集

Data Collection Project Ideas & Demos Tech With Tim

数据标注

ROC and AUC, Clearly Explained! StatQuest with Josh Starmer
145 - Confusion matrix, ROC and AUC in machine learning DigitalSreeni
实操揭秘数据标注项目的套路，有点得罪人了，阅后删 月下跑项目
Image Annotation for Machine Learning Apeer_micro
label encoding, 把标签变成数字

数据增强

RubanSeven/Text-Image-Augmentation-python

数据不均衡 imbalanced data

149 - Working with imbalanced data for ML - Demonstrated using liver disease data DigitalSreeni
类别不平衡 南京大学周志华 Darics
过采样, oversampling smote 欠采样, undersampling EasyEnsemble 阈值移动, threshold moving

数据可视化

Data Visualization with D3 – Full Course for Beginners [2022] freeCodeCamp
Data Visualization with D3.js - Full Tutorial Course(freeCodeCamp) 老版本
Tutorial: Real Time Data Visualization - d3, crossfilter, websockets in Python by Example
Other Level’s u
DataV Vue　git v
CNN Explainer s v
dair-ai/ml-visuals doc wx 链接: https://pan.baidu.com/s/1CC6BFfiw0DcyVfYTofmH9A 提取码: r4z3
Visualization and Interactive Dashboard in Python: My favorite Python Viz tools — HoloViz Sophia Yang
pyviz
Viz Sophia Yang
ContextLab/hypertools 用于获得对高维数据的几何洞察力的 Python 工具箱
Vispy s git
Matplotlib
How to Create a Beautiful Python Visualization Dashboard With Panel/Hvplot Thu Vu data analytics
szagoruyko/pytorchviz colab
Plotly
Data Visualization Using Python BOKEH | Python Bokeh Dashboard | Full Course Tangoo Express
Python数据可视化详解大全-从简单到完善到高级设置（Matplotlib/Seaborn/Plotly/常用统计图形）云开见明教育科技
Automatically Visualize Datasets with AutoViz in Python NeuralNine
EdrawMax v
Python Data Analysis Projects for 2022 | Data Analysis With Python | Python Training | Simplilearn
Build a Media Analysis Dashboard with Python & Cloudinary Patrick Loeber
Longer lessons storytelling with data
Data Visualisation Luci Date
Interactive Web Visualizations with Bokeh in Python NeuralNine
[Tutorialsplanet.NET] Udemy - 2022 Python Data Analysis & Visualization Masterclass
[Tutorialsplanet.NET] Udemy - The Complete Data Visualization Course 2020
Visualizing Binary Data with 7-Segment Displays Sebastian Lague
🔴 Visualizing Data Structures and Algorithms with VS Code Visual Studio Code
Data Visualization Tutorial Krish Naik using Qliksense
Data Visualisation Luci Date
D3 JS - Build Data Driven Visualizations with Javascript [svg animation, data engineering] Build Apps With Paulo
Plotnine: A Different Approach To Data Visualization in Python NeuralNine
7 Python Data Visualization Libraries in 15 minutes Rob Mulla
Machine Learning Course - Lesson 2: Visualizing Data with JavaScript Radu Mariescu-Istodor
Create Interactive Maps & Geospatial Data Visualizations With Python | Real Python Podcast #143 Real Python
Build a Chart using JavaScript (No Libraries) Radu Mariescu-Istodor
Machine Learning Model Evaluation in JavaScript Radu Mariescu-Istodor
Machine Learning Course Radu Mariescu-Istodor

Tableau
Tableau 是一个可视化分析平台，它改变了我们使用数据解决问题的方式，使个人和组织能够充分利用自己的数据。
Tableau in Two Minutes - Tableau Basics for Beginners Penguin Analytics
How to create Radial Chart in Tableau| Step-by-step Megha Narang
Tableau数据可视化，学完就掌握商业分析必备技能了！（第613期） Data Application Lab
Tableau零基础教程 未明学院

Gourcer s u	a software version control visualization tool

电子教鞭
inux下netmeeting
红烛电子教鞭
deepin-draw
pointofix

部署 Deploy

How to Deploy Machine Learning Apps? Normalized Nerd
Kevin Goetsch | Deploying Machine Learning using sklearn pipelines PyData
Talk | 清华大学在读博士生胡展豪：可以骗过人工智能检测器的隐身衣 将门-TechBeat技术社区
Deploy ML Models from Colab with FastAPI & ColabCode - Free ML as a Service 1littlecoder
Run Your Flask App In Google Colab | [ Updated Way ] Cyber Creed
How to run Google Colab or Kaggle notebooks on VSCODE (My experience running example code on GPU) convergeML
Deploying production ML models with TensorFlow Serving overview TensorFlow
Deployment of ML Models Krish Naik
Aladdin Persson u
Build & Deploy AI SaaS with Reoccurring Revenue (Next.js, OpenAI, Stripe, Tailwind, Vercel) freeCodeCamp
How to Deploy a Web App Using Multiple Methods (Azure, Render, MongoDB Atlas, Koyeb, and more ) freeCodeCamp
👍AI 项目本地部署-通用脚本🟢小白都能用 🟢 通吃GitHub上的AI相关项目🟢 Step by Step 一个脚本搞定 🟢 AI项目本地部署保成功 NiuGee AI
Deploy Python Applications - Google Cloud Run with Docker NeuralNine
Deploy Python Applications From Source - Google Cloud Run NeuralNine
Edge AI 開發板挑選完整指南 VisCircuit 電路筆記

TensorRT

TensorRT是英伟达（NVIDIA）推出的深度学习推理加速库，它针对深度学习模型的推理阶段进行了优化。TensorRT（TensorRT是Tensor Runtime的缩写）可以通过高度优化的网络层和推理算法，提供低延迟和高吞吐量的深度学习推理性能。 TensorRT的主要功能包括： 网络优化：TensorRT可以通过对模型进行层级优化、融合相邻层、剪枝和量化等技术，来提高模型的推理性能。它可以自动检测并融合相似操作，减少了内存带宽和计算需求。 精度校准：TensorRT支持对模型进行精度校准，从而在保持模型准确性的同时，进一步优化推理性能。它可以通过减少浮点运算的位数或者使用定点数表示来降低计算复杂度。 动态尺寸支持：TensorRT可以处理具有可变输入尺寸的模型。这意味着可以根据实际输入的尺寸动态调整网络的计算图和内存分配。 多平台和多框架支持：TensorRT可以与多个深度学习框架（如TensorFlow、PyTorch和Caffe）无缝集成，同时支持多个硬件平台（包括NVIDIA的GPU和DPU）。 使用TensorRT可以显著提高深度学习模型的推理速度和效率，特别适用于需要实时性能的应用场景，如自动驾驶、工业自动化、物体检测和视频分析等。 总之，TensorRT是一个优化深度学习推理的强大工具，它通过网络优化、精度校准和动态尺寸支持等功能，提供高性能的推理加速，从而加快了深度学习模型在实际应用中的部署和执行速度。
TensorRT更加偏向于深度学习模型的部署阶段。它专注于对已经训练好的模型进行优化和加速，以提高模型在推理阶段的性能和效率。
NVIDIA TensorRT: High Performance Deep Learning Inference NVIDIA Developer

扩散模型 Diffusion models

【AIGC】七千字通俗讲解Stable Diffusion | 稳定扩散模型 | CLIP | UNET | VAE | Dreambooth | LoRA 最佳拍档
Talk | 北京大学杨灵：扩散生成模型的方法、关联与应用 将门-TechBeat技术社区
Diffusion models explained in 4-difficulty levels AssemblyAI
DDPM - Diffusion Models Beat GANs on Image Synthesis (Machine Learning Research Paper Explained) Yannic Kilcher
Ultimate Guide to Diffusion Models | ML Coding Series | Denoising Diffusion Probabilistic Models The AI Epiphany
Diffusion models The AI Epiphany
Exploring the NEW Hugging Face Diffusers Package | Diffusion Models w/ Python Nicholas Renotte
Stable Diffusion - What, Why, How? Edan Meyer 54:07 colab
由浅入深了解Diffusion Model ewrfcas
Creating Stable Diffusion Interpolation Videos sentdex
midjourney v
[ML News] Stable Diffusion Takes Over! (Open Source AI Art) Yannic Kilcher
Stable Diffusion AI画图 LKs OFFICIAL CHANNEL s ERNIE-ViLG s git s
CompVis/stable-diffusion v Hugging Face
Harmonai, Dance Diffusion and The Audio Generation Revolution Weights & Biases
AI艺术 抖音号： 1764700788 askNK u
Google's AI: Stable Diffusion On Steroids! 💪 Two Minute Papers
30年前游戏角色画风一键升级！从粗糙像素风变成高清建模画风 量子位
Diffusion Models | Paper Explanation | Math Explained Outlier
Diffusion models from scratch in PyTorch DeepFindr
JEPA - A Path Towards Autonomous Machine Intelligence (Paper Explained) Yannic Kilcher
Google's DreamFusion AI: Text to 3D sentdexGoogle's DreamFusion AI: Text to 3D sentdex
I tried to build a REACT STABLE DIFFUSION App in 15 minutes Nicholas Renotte
Stable Diffusion Is Getting Outrageously Good! 🤯 Two Minute Papers
Stable Diffusion Version 2: Power To The People… For Free! Two Minute Papers
[ML News] Multiplayer Stable Diffusion | OpenAI needs more funding | Text-to-Video models incoming Yannic Kilcher
Google's Prompt-to-Prompt: Diffusion Image Editing sentdex
Diffusion Model 수학이 포함된 tutorial 디퓨전영상올려야지
Stable Diffusion in Code (AI Image Generation) - Computerphile
AI换脸，AI去马赛克是如何实现的？初识人工智能大火算法-扩散模型 基地
Diffusion and Score-Based Generative Models MITCBMM
Generative Adversarial Networks (GANs) and Stable Diffusion TensorFlow
Diffusion Models - Live Coding Tutorial dtransposed Diffusion Models - Live Coding Tutorial 2.0 dtransposed
Kas Kuo Lab u
MIT 6.S192 - Lecture 22: Diffusion Probabilistic Models, Jascha Sohl-Dickstein Ali Jahanian
Diffusion Models for Inverse Problems Inference & Control Group Planning with Diffusion for Flexible Behavior Synthesis Inference & Control Group Hierarchically branched diffusion models Inference & Control Group Diffusion models as plug-and-play priors Inference & Control Group
Tutorial on Denoising Diffusion-based Generative Modeling: Foundations and Applications Arash Vahdat
【stable diffusion】由淺入深了解Diffusion擴散模型 HKCTO 唐宇迪
AI Art Taking World By Storm - Diffusion Models Overview deeplizard AI Art for Beginners - Stable Diffusion Crash Course deeplizard
CS 198-126: Lecture 12 - Diffusion Models Machine Learning at Berkeley
What are Diffusion Models? Ari Seff
Talk | MIT许逸伦：解锁由物理启发的深度生成模型-从扩散模型到泊松流模型 将门-TechBeat技术社区
[專題解說] Introduction to Diffusion Model 擴散模型入門 [附程式碼] 教學 工gin師
號稱打敗 GAN 的生成模型: Diffusion Models TJWei

Stable Diffusion
Stable Diffusion Online s
CompVis/stable-diffusion
AI Art with Stable Diffusion (Women of the World) deeplizard
最火的AI作图模型，这5款免费下载，含提示词，配合 Stable-diffusion 来制作高清大图吧！ | 零度解说
Generating Realistic AI Images with Stable Diffusion NeuralNine
为什么AI画画能既离谱又烧钱啊？？ 量子位
Stable Diffusion不用獨立顯卡，不需上網連線，10分鐘超簡單安裝教學就把AI繪圖搬回家，有NVIDIA獨顯繪畫更快，Stable Diffusion能單機使用，比Midjourney好用 老阿貝
Lesson 9: Deep Learning Foundations to Stable Diffusion, 2022 Jeremy Howard
由Stabiliti AI在2022年发布的工具 u 抓取了50亿公开图片, 可以用文字和图片生成图片 colab Chillout_mix civitai
云端AI绘图软件+本地Stable Diffusion免安装版+懒人常用模型包,完全使用攻略-猩猩看了都会用的AI绘图视频教程 番茄市常听
AI For You u
Easiest Way To Install Stable Diffusion & Generate AI Images NeuralNine
教你用 Google colab 免費玩 Stable Diffusion 作出擬真美女圖片！ Lora、ControlNet 教學（iPhone、Android、筆電、Mac 均適用） 電腦王阿達
Stable Diffusion XL v
JW608 Plays With Stable Diffusion! JW608
[Stable Diffusion AI畫圖插件] Composable LoRA加強版! 支援LoCon、LyCORIS，並能讓LoRA只在特定步數作用! 張宇帆
Stable Diffusion教學 使用Lora製作AI網紅 Kas Kuo Lab
Stable Diffusion 教學 Kas Kuo Lab
AI绘画】给美女们更换衣服 零度解说
Stable Diffusion Tutorials, Automatic1111 Web UI & Google Colab Guides, DreamBooth, Textual Inversion / Embedding, LoRA, AI Upscaling, Video to Anime SECourses
Stable Diffusion Got Supercharged - For Free! Two Minute Papers
​生成扩散模型漫谈：条件控制生成结果 PaperWeekly 有参考文献
生成扩散模型漫谈（九）：条件控制生成结果 spaces
生成扩散模型漫谈（十七）：构建ODE的一般步骤（下） spaces
工gin師 u DiffusionModel 工gin師 Stable Diffusion 系列 工gin師
Mac上最好用的StableDiffusion客户端，Draw Things详细演示！The best local AI painting Stable DIffusion client Intro. 工具狂Toolbuddy
Stable Diffusion 進階教學：Colab 如何套 Lora、動漫圖真人化、網拍模特不求人、黑白線稿自動上色 電腦王阿達
Stable Diffusion教程 从入门到精通 氪学家 Stable Diffusion 电商系列课程 氪学家
真人LORA训练全攻略！看这篇就够了 LORA模型 Stable diffusion 教程 真人模型 阿硕讲AI
大白话AI | 图像生成模型之DDPM | 扩散模型 | 生成模型 | 概率扩散去噪生成模型 | Diffusion Model

MultiDiffusion
MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation s arxiv git
pkuliyi2015/multidiffusion-upscaler-for-automatic1111 高清放大插件MultiDiffusion 小显存也能跑出4k图 低配福音 赛博法师

基础模型 Foundation Models Large Models

火遍全网的AI大模型，华为能搞出什么新花样？老石谈芯
AI大模型是什么？可以让人工智能和人类一样？GPT-3、M6大模型 啃芝士
#84 LAURA RUIS - Large language models are not zero-shot communicators [NEURIPS UNPLUGGED] Machine Learning Street Talk
Talk | 微信AI高级研究员苏辉：微信AI大规模预训练语言模型WeLM 将门-TechBeat技术社区
Real World Applications of Large Models Weights & Biases
Foundation models and the next era of AI Microsoft Research
Emily M. Bender — Language Models and Linguistics Weights & Biases

多模态 Multi-modal

多模态论文串讲·上【论文精读】 Mu Li 跟李沐学AI
多模态论文串讲·下【论文精读】 Mu Li
CLIP 论文逐段精读【论文精读】 Mu Li
CLIP 改进工作串讲（上）【论文精读】Mu Li
CLIP 改进工作串讲（下）【论文精读】 Mu Li
ViLT 论文精读【论文精读】 Mu Li
ViT论文逐段精读【论文精读】 Mu Li mli/paper-reading
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale (Paper Explained) Yannic Kilcher
AI Hairball - ChatGPT + Stable Diffusion deeplizard
Talk | 东京大学博士生刘海洋：多模态驱动谈话动作生成-质量与多样性 将门-TechBeat技术社区
OpenAI CLIP Explained | Multi-modal ML James Briggs
Fast Zero Shot Object Detection with OpenAI CLIP James Briggs
OpenAI's CLIP for Zero Shot Image Classification James Briggs
Fast intro to multi-modal ML with OpenAI's CLIP James Briggs
OpenAI CLIP: ConnectingText and Images (Paper Explained) Yannic Kilcher
Domain-Specific Multi-Modal Machine Learning with CLIP Pinecone
CLIP: Connecting Text and Images Connor Shorten
OpenAI CLIP - Connecting Text and Images | Paper Explained Aleksa Gordić - The AI Epiphany
OpenAI’s CLIP explained! | Examples, links to code and pretrained model AI Coffee Break with Letitia
Talk | 微软高级研究员杨征元：统一的视觉语言模型 将门-TechBeat技术社区
Vision Transformer (ViT) 用于图片分类 Shusen Wang
Vision Transformers (ViT) Explained + Fine-tuning in Python James Briggs

ImageBind Meta AI

只有Meta才懂多模态，ImageBind，在一个嵌入的空间中补齐六种模态。像人一样，感受完整的空间。突破语言的桎梏，将关注度重新吸引回元宇宙。 老范讲故事
【分享】LLM论文研读 | ImageBind One Embedding Space To Bind Them All | 六种模态大统一 | Kevin分享 | Meta AI 最佳拍档
arxiv
facebookresearch/ImageBind
ImageBind: a new way to ‘link’ AI across the senses meta

AI Safety

AI Safety Times Infinity
【機器學習2022】自然語言處理上的對抗式攻擊 (由姜成翰助教講授) Hung-yi Lee 1 2
Talk | 清华大学在读博士生胡展豪：可以骗过人工智能检测器的隐身衣 将门-TechBeat技术社区
Talk | 几何的魅力: 黑盒攻击新策略 将门-TechBeat技术社区

ML会议

Steven Van Vaerenbergh u

CVPR

NIPS

ICLR

ICML

ACML

NeurIPS

MLSP

CompSci 188

CompSci 188 Shital Shah

谷歌学术标签

machine_learning	artificial_intelligence	deep_learning
data_science	high_performance_computing	statistical_data_analysis
particle_physics	quantum_computing	physics
time_series_analysis	optimization	control
time_series
algorithms	control_systems	control_theory
mathematics	mathematical_optimization	statistics
signal_processing	information_theory	probability
computer_science	finance	fpga
cryptography	game_theory	traveling_salesman_problem
swarm_intelligence	data_mining	swarm_robotics
ai	econometrics	evolutionary_robotics
reinforcement_learning	neural_networks	autonomous_cars
generative_models	variational_inference	monte_carlo_simulation
computer_vision	pattern_recognition	software_architecture
medical_imaging	graph	big_data
image_restoration	statistical_modeling	image_compression
	image_and_video_coding	data_compression
multimedia_coding	compression	high_resolution_imaging

Book

神经网络与深度学习(s, 翻译, )
复旦大学邱锡鹏教授的《神经网络与深度学习》 人工智能学习室 19:05:43
HyperDL-Tutorial(git, 书栈, )
机器学习实战（Machine Learning in Action） (书栈, )
Interpretable Machine Learning (书栈, )
ML Kit 中文文档 (书栈, )
spark机器学习算法研究和源码分析 (书栈, )
ml5.js - Machine Learning for Web (书栈, )
机器学习训练秘籍（Machine Learning Yearning 中文版） (书栈, )
Pipcook v1.0 机器学习工具使用教程 (书栈, )
DeepLearning-500-questions(jd, 2, )
Deeplearning Algorithms Tutorial（深度学习算法教程） (书栈, git, )
花书 deeplearningbook(s, )
神经网络的损失函数为什么是非凸的?（知乎）
awesome-material git
foochane/books git
lovingers/ML_Books git 差评
深度学习入门-基于Python的理论与实现 deep-learning-from-scratch git

周志华 机器学习 西瓜书

【一起啃书】机器学习西瓜书白话解读 致敬大神 13:10:47
周志华《机器学习》学习笔记 书栈 git git
南瓜书 datawhalechina/pumpkin-book s
南京大学周志华教授亲讲 Darics 6:20:50 机器学习初步- 南京大学- 学堂在线 机器学习-周志华-学习记录-第一章绪论 小瘪️ csdn
【完整版-南京大学-机器学习】全66讲 OpenCV图像处理 58:28:56
南京大学周志华完整版100集【机器学习入门教程】人工智能-研究所 96:21:52
周志华《机器学习》西瓜书+李航《统计学习方法》 CV前沿与深度学习 54:56:53
南京大学人工智能学院院长周志华《机器学习西瓜书》白话解读，一起啃书！ AI技术星球 28:27:48

MLAPP

Machine Learning A Probabilistic Perspective
第一章 介绍 一 二 三 四
第二章 概率 一 二 三 四
第三章 基于离散数据的生成模型 一 二 三
第四章 高斯模型
第五章 贝叶斯方法
第六章 频率统计方法
第七章 线性回归
第八章 逻辑回归
第九章 广义线性模型
第十章 有向图模型
第十一章 混合模型与EM算法
第十二章 隐线性模型
第十三章 稀疏线性模型
第十四章 Kernels
第十五章 Gaussian Process
第十六章 自适应基函数模型
第十七章 隐马尔可夫模型
第十八章 状态空间模型
第十九章 无向图模型
第二十章 图模型的确切推断

花书

MingchaoZhu/DeepLearning 数学推导、原理剖析与源码级别代码实现

31MB

深度学习.pdf

PDF

打开

百面深度学习

57MB

百面深度学习：算法工程师带你去面试_.pdf

PDF

打开

百面机器学习

25MB

百面机器学习算法工程师带你去面试.pdf

PDF

打开

统计学习方法

求推荐一部以李航的《统计学习方法》为教材的教学视频？知乎
深度之眼《统计学习方法》第二版啃书指导视频 深度之眼官方账号 08:55:48
大数据机器学习（袁春）电子工程世界 共113课时 15小时39分33秒 MM li
《统计学习方法》第二版的代码实现 git
《统计学习方法·第2版》手推公式+算法实例+Python实现 喜欢AI的程序猿 22h
统计学习 Statistical Learning Stanford Online
周志华《机器学习》西瓜书+李航《统计学习方法》 CV前沿与深度学习 54:56:53

PRML

PRML/PRMLT s Matlab code of machine learning algorithms in book PRML zh

ESL

其他

人工智能时代 李开复 Acsic People
2020 Machine Learning Roadmap (still valid for 2021) Daniel Bourke
Why AI is Harder Than We Think (Machine Learning Research Paper Explained) Yannic Kilcher
Discovering ketosis: how to effectively lose weight git
imhuay/studies 学习笔记 git
25th-engineer/DaChuangFiles git
MLEveryday/100-Days-Of-ML-Code 机器学习100天 en topic git git git
How to Do Freelance AI Programming Siraj Raval
Qinbf/deeplearning_paper
Variational Autoencoders - EXPLAINED! CodeEmporium
guillaume-chevalier/Awesome-Deep-Learning-Resources
什么是 MLOps? Morgan Yong
MLOps Aleksa Gordić - The AI Epiphany
Productionize Your ML Workflows with MLOps Tools Weights & Biases
ml-tooling/best-of-ml-python 项目包括：机器学习框架、数据可视化、图像、NLP和文本、图、金融领域、时间序列等等，内容非常全
7 FREE A.I. tools for YOU today! (plus 1 bonus!) Artificial Intelligence and Blockchain
The Age of A.I. YouTube Originals
The History of Artificial Intelligence [Documentary] Futurology — An Optimistic Future
Artificial Intelligence: Exploring the Pros and Cons for a Smarter Future Things to Know

Yoshua Bengio

From Deep Learning of Disentangled Representations to Higher-level Cognition Microsoft Research

Geoffrey Hinton

A Fireside Chat with Turing Award Winner Geoffrey Hinton, Pioneer of Deep Learning (Google I/O'19) TensorFlow

Geoff Hinton explains the Forward-Forward Algorithm Eye on AI

Geoff Hinton on Forward-Forward Eye on AI

This Algorithm Could Make a GPT-4 Toaster Possible Edan Meyer

Full interview: "Godfather of artificial intelligence" talks impact and potential of AI CBS Mornings

Geoffrey Hinton: The Foundations of Deep Learning Elevate

深入学习英雄: 吴恩达采访 Geoffrey Hinton Preserve Knowledge

This Canadian Genius Created Modern AI Bloomberg Originals

Andrew Ng

Andrew Ng: Deep Learning, Education, and Real-World AI | Lex Fridman Podcast #73

Andrew Ng: Advice on Getting Started in Deep Learning | AI Podcast Clips Lex Fridman

Michael I. Jordan

Michael I. Jordan: Machine Learning, Recommender Systems, and Future of AI | Lex Fridman Podcast #74

Yann LeCun

Yann LeCun u

Yann LeCun: "A Path Towards Autonomous AI", Baidu 2022-02-22

Yann LeCun: Deep Learning, ConvNets, and Self-Supervised Learning | Lex Fridman Podcast #36

Yann LeCun: Dark Matter of Intelligence and Self-Supervised Learning | Lex Fridman Podcast #258

Yann LeCun Lecture 8/8 Unsupervised Learning trwappers

John Carmack will Develop True Artificial Intelligence. Here is Why Machine Learning with Phil

Is ChatGPT A Step Toward Human-Level AI? — With Yann LeCun, Meta Chief AI Scientist Alex Kantrowitz