| description |
|---|
机器学习 |
AI之禅 机器之心 ATYUN订阅号 AI科技大本营的专栏 BestSDK 云+直播
| 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)
| Carnegie Mellon University Deep Learning u | |
| Deep Learning(quora, ) | Supervisely u |
| Ping Data Science(quora, ) | Data Engineering Minds(quora, ) |
| Data Sciences - Analytics(quora, ) | Data Analytics or EnGines(quora, ) |
| Data Science in Marketing(quora, ) | |
| 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 |
| 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． |
| 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), ) |
| 茶米老師教室 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 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 |
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(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 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(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 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 |
Artificial Intelligence (AI) vs Machine Learning vs Deep Learning vs Data Science codebasics
机器学习算法地图 SIGAI
| 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 - 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 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 |
| 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 |
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"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。 |
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LSTM
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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 |
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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
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| SimCLR sota |
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Ali Ghodsi, Lec : Deep Learning, Variational Autoencoder, Oct 12 2017 [Lect 6.2] |
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| 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) |
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| 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 |
| 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 |
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：
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 |
| 【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 |
| 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 |
| 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 |
| 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 |
| 多模态论文串讲·上【论文精读】 Mu Li 跟李沐学AI |
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| CLIP 论文逐段精读【论文精读】 Mu Li |
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| 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 |
| 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 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 |
| Steven Van Vaerenbergh u |
| CompSci 188 Shital Shah |
| 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 |
| 【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 |
| 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 |
MingchaoZhu/DeepLearning 数学推导、原理剖析与源码级别代码实现
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{% file src="../.gitbook/assets/百面深度学习：算法工程师带你去面试_.pdf" %}
{% file src="../.gitbook/assets/百面机器学习算法工程师带你去面试.pdf" %}
| 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/PRMLT s Matlab code of machine learning algorithms in book PRML zh
ESL
| 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