├── images ├── readme.md ├── LLM.png ├── NLP.jpg ├── MLOps.png ├── Data Science.png ├── Computer Vision.png ├── Data Engineering.jpg ├── Machine Learning.jpg └── Awosme ML GitHub Repos.png ├── LICENSE └── readme.md /images/readme.md: -------------------------------------------------------------------------------- 1 | 2 | -------------------------------------------------------------------------------- /images/LLM.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/youssefHosni/Awesome-AI-Data-GitHub-Repos/HEAD/images/LLM.png -------------------------------------------------------------------------------- /images/NLP.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/youssefHosni/Awesome-AI-Data-GitHub-Repos/HEAD/images/NLP.jpg -------------------------------------------------------------------------------- /images/MLOps.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/youssefHosni/Awesome-AI-Data-GitHub-Repos/HEAD/images/MLOps.png -------------------------------------------------------------------------------- /images/Data Science.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/youssefHosni/Awesome-AI-Data-GitHub-Repos/HEAD/images/Data Science.png -------------------------------------------------------------------------------- /images/Computer Vision.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/youssefHosni/Awesome-AI-Data-GitHub-Repos/HEAD/images/Computer Vision.png -------------------------------------------------------------------------------- /images/Data Engineering.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/youssefHosni/Awesome-AI-Data-GitHub-Repos/HEAD/images/Data Engineering.jpg -------------------------------------------------------------------------------- /images/Machine Learning.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/youssefHosni/Awesome-AI-Data-GitHub-Repos/HEAD/images/Machine Learning.jpg -------------------------------------------------------------------------------- /images/Awosme ML GitHub Repos.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/youssefHosni/Awesome-AI-Data-GitHub-Repos/HEAD/images/Awosme ML GitHub Repos.png -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | 2 | MIT License 3 | 4 | Copyright (c) Microsoft Corporation. 5 | 6 | Permission is hereby granted, free of charge, to any person obtaining a copy 7 | of this software and associated documentation files (the "Software"), to deal 8 | in the Software without restriction, including without limitation the rights 9 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 10 | copies of the Software, and to permit persons to whom the Software is 11 | furnished to do so, subject to the following conditions: 12 | 13 | The above copyright notice and this permission notice shall be included in all 14 | copies or substantial portions of the Software. 15 | 16 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 17 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 18 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 19 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 20 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 21 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 22 | SOFTWARE 23 | -------------------------------------------------------------------------------- /readme.md: -------------------------------------------------------------------------------- 1 | # Awesome AI & Data GitHub-Repos [![Awesome](https://awesome.re/badge.svg)](https://awesome.re) 2 | A curated list of the most essential GitHub repos that cover the AI & ML landscape. If you like to add or update projects, feel free to open an issue or submit a pull request. Contributions are very welcome! 3 | 4 | 5 | [![GitHub license](https://img.shields.io/github/license/youssefHosni/Awesome-ML-GitHub-Repos.svg)](https://github.com/youssefHosni/Awesome-ML-GitHub-Repos/blob/master/LICENSE) 6 | [![GitHub contributors](https://img.shields.io/github/contributors/youssefHosni/Awesome-ML-GitHub-Repos.svg)](https://GitHub.com/youssefHosni/Awesome-ML-GitHub-Repos/graphs/contributors/) 7 | [![GitHub issues](https://img.shields.io/github/issues/youssefHosni/Awesome-ML-GitHub-Repos.svg)](https://GitHub.com/youssefHosni/Awesome-ML-GitHub-Repos/issues/) 8 | [![GitHub pull-requests](https://img.shields.io/github/issues-pr/youssefHosni/Awesome-ML-GitHub-Repos.svg)](https://GitHub.com/youssefHosni/Awesome-ML-GitHub-Repos/pulls/) 9 | [![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com) 10 | 11 | [![GitHub watchers](https://img.shields.io/github/watchers/youssefHosni/Awesome-ML-GitHub-Repos.svg?style=social&label=Watch)](https://GitHub.com/youssefHosni/Awesome-ML-GitHub-Repos/watchers/) 12 | [![GitHub forks](https://img.shields.io/github/forks/youssefHosni/Awesome-ML-GitHub-Repos.svg?style=social&label=Fork)](https://GitHub.com/youssefHosni/Awesome-ML-GitHub-Repos/network/) 13 | [![GitHub stars](https://img.shields.io/github/stars/youssefHosni/Awesome-ML-GitHub-Repos.svg?style=social&label=Star)](https://GitHub.com/youssefHosni/Awesome-ML-GitHub-Repos/stargazers/) 14 | 15 | [![Substack](https://img.shields.io/badge/Substack-%23006f5c.svg?style=for-the-badge&logo=substack&logoColor=FF6719)](https://youssefh.substack.com/) 16 | [![Medium](https://img.shields.io/badge/Medium-12100E?style=for-the-badge&logo=medium&logoColor=white)](https://medium.com/@yousefhosni) 17 | [![Kaggle](https://img.shields.io/badge/Kaggle-035a7d?style=for-the-badge&logo=kaggle&logoColor=white)](https://www.kaggle.com/youssef19) 18 | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/channel/UCeEcSgRzYFuVt-2Yk1ULdhQ) 19 | 20 | 21 | ![alt text](https://github.com/youssefHosni/Awesome-ML-GitHub-Repos/blob/main/images/Awosme%20ML%20GitHub%20Repos.png) 22 | 23 | ## Table of Contents: 24 | * [Natural Language Processing (NLP)](https://github.com/youssefHosni/Awesome-ML-GitHub-Repos/blob/main/readme.md#:~:text=Data%20Engineering-,Natural%20Language%20Processing,-nlp%2Dtutorial%3A%20nlp) 25 | * [Large Language Models(LLM)](https://github.com/youssefHosni/Awesome-ML-GitHub-Repos/blob/main/readme.md#:~:text=lines%20of%20code.-,Large%20Language%20Models,-Open%20LLMs%3A%20List) 26 | * [Computer Vision](https://github.com/youssefHosni/Awesome-ML-GitHub-Repos/blob/main/readme.md#:~:text=LLMs%20through%20composability-,Computer%20Vision,-Computer%20Vision%20Tutorials) 27 | * [Data Science](https://github.com/youssefHosni/Awesome-ML-GitHub-Repos/blob/main/readme.md#:~:text=based%20CV%20works-,Data%20Science,-Data%20Science%20for) 28 | * [Machine Learning](https://github.com/youssefHosni/Awesome-ML-GitHub-Repos/blob/main/readme.md#:~:text=Interview%20Questions%20Answers-,Machine%20Learning,-Best%2Dof%20Machine) 29 | * [Machine Learning Projects](https://github.com/youssefHosni/Awesome-AI-Data-GitHub-Repos/blob/main/readme.md#:~:text=Machine%20Learning%20Books-,Machine%20Learning%20Projects,-Orca%20calls%20Classifier) 30 | * [Machine Learning Engineerings Operations (MLOps)](https://github.com/youssefHosni/Awesome-ML-GitHub-Repos/blob/main/readme.md#:~:text=Machine%20Learning%20Interviews-,Machine%20Learning%20Engineerings%20Operations%20(MLOps),-MLOps%2DBasics) 31 | * [Data Engineering](https://github.com/youssefHosni/Awesome-ML-GitHub-Repos/blob/main/readme.md#:~:text=MLOps%20Course-,Data%20Engineering,-Data%20Engineering%20Zoomcamp) 32 | * [SQL & Database](https://github.com/youssefHosni/Awesome-AI-Data-GitHub-Repos/blob/main/readme.md#:~:text=Engineering%20Interview%20Questions-,SQL%20%26%20Database,-SQL%20101%20by) 33 | * [Statistics](https://github.com/youssefHosni/Awesome-AI-Data-GitHub-Repos#:~:text=Scientists%20by%20gvwilson-,Statistics,-Practical%20Statistics%20for) 34 | 35 | ## Natural Language Processing ## 36 | ![alt text](https://github.com/youssefHosni/Awesome-ML-GitHub-Repos/blob/main/images/NLP.jpg) 37 | 38 | * [nlp-tutorial](https://github.com/graykode/nlp-tutorial): nlp-tutorial is a tutorial for who is studying NLP(Natural Language Processing) using Pytorch. Most NLP models were implemented with less than 100 lines of code. 39 | 40 | ## Large Language Models ## 41 | ![alt text](https://github.com/youssefHosni/Awesome-ML-GitHub-Repos/blob/main/images/LLM.png) 42 | * [LLMs Practical Guide: The Practical Guides for Large Language Models](https://github.com/Mooler0410/LLMsPracticalGuide) 43 | * [LLM Survey: A collection of papers and resources related to Large Language Models](https://github.com/RUCAIBox/LLMSurvey) 44 | * [Open LLMs: List of LLMs that are all licensed for commercial](https://github.com/eugeneyan/open-llms) 45 | * [Awesome LLM: Curated list of papers about large language models, especially relating to ChatGPT](https://github.com/Hannibal046/Awesome-LLM) 46 | * [Awesome Decentralized LLM: Collection of LLM resources that can be used to build products you can "own" or to perform reproducible research](https://github.com/imaurer/awesome-decentralized-llm) 47 | * [LangChain: Building applications with LLMs through composability](https://github.com/hwchase17/langchain) 48 | * [Awesome LangChain: Curated list of tools and projects using LangChain](https://github.com/kyrolabs/awesome-langchain) 49 | * [Awesome-Graph-LLM: A collection of AWESOME things about Graph-Related Large Language Models (LLMs).](https://github.com/XiaoxinHe/Awesome-Graph-LLM) 50 | * [DemoGPT: Auto Gen-AI App Generator with the Power of Llama 2](https://github.com/melih-unsal/DemoGPT) 51 | * [OpenLLM: An open platform for operating large language models (LLMs) in production](https://github.com/bentoml/OpenLLM) 52 | * [LLM Zoo: democratizing ChatGPT](https://github.com/FreedomIntelligence/LLMZoo) 53 | * [VectorDB-recipes](https://github.com/lancedb/vectordb-recipes) 54 | * [Awesome GPT Prompt Engineering: A curated list of awesome resources, tools, and other shiny things for GPT prompt engineering](https://github.com/snwfdhmp/awesome-gpt-prompt-engineering) 55 | * [Prompt Engineering Guide: ](https://github.com/dair-ai/Prompt-Engineering-Guide) 56 | * [LLM Course](https://github.com/mlabonne/llm-course) 57 | 58 | ## Computer Vision ## 59 | ![alt text](https://github.com/youssefHosni/Awesome-ML-GitHub-Repos/blob/main/images/Computer%20Vision.png) 60 | * [Awesome Computer Vision: A curated list of awesome computer vision resources](https://github.com/jbhuang0604/awesome-computer-vision) 61 | * [Computer Vision Tutorials by Roboflow](https://github.com/roboflow/notebooks) 62 | * [Transformer in Vision: paper list of some recent Transformer-based CV works](https://github.com/Yangzhangcst/Transformer-in-Computer-Vision) 63 | * [Awesome-Referring-Image-Segmentation: A collection of referring image segmentation papers and datasets](https://github.com/MarkMoHR/Awesome-Referring-Image-Segmentation) 64 | * [awesome-vision-language-pretraining-papers: Recent Advances in Vision and Language PreTrained Models (VL-PTMs)](https://github.com/yuewang-cuhk/awesome-vision-language-pretraining-papers) 65 | * [Awesome Vision-and-Language: A curated list of awesome vision and language resources,](https://github.com/sangminwoo/awesome-vision-and-language) 66 | * [Awesome-Temporal-Action-Detection-Temporal-Action-Proposal-Generation](https://github.com/zhenyingfang/Awesome-Temporal-Action-Detection-Temporal-Action-Proposal-Generation) 67 | * [Awesome-Referring-Image-Segmentation: A collection of referring image segmentation papers and datasets.](https://github.com/MarkMoHR/Awesome-Referring-Image-Segmentation) 68 | * [Awesome Masked Autoencoders: A collection of literature after or concurrent with Masked Autoencoder (MAE) ](https://github.com/EdisonLeeeee/Awesome-Masked-Autoencoders) 69 | * [Awesome Visual-Transformer: Collection of some Transformer with Computer-Vision (CV) papers](https://github.com/dk-liang/Awesome-Visual-Transformer) 70 | * [Transformer-Based Visual Segmentation: A Survey](https://github.com/lxtGH/Awesome-Segmentation-With-Transformer) 71 | * [Awesome-Segmentation-With-Transformer](https://github.com/lxtGH/Awesome-Segmentation-With-Transformer) 72 | * [CVPR 2o23 Paper with Code](https://github.com/amusi/CVPR2023-Papers-with-Code) 73 | * [Awesome Deepfakes Detection](https://github.com/Daisy-Zhang/Awesome-Deepfakes-Detection) 74 | * [Weekly-Top-Computer-Vision-Papers](https://github.com/youssefHosni/Weekly-Top-Computer-Vision-Papers) 75 | 76 | ## Data Science ## 77 | ![alt text](https://github.com/youssefHosni/Awesome-ML-GitHub-Repos/blob/main/images/Data%20Science.png) 78 | 79 | * [Data Science for Beginners - A Curriculum](https://github.com/microsoft/Data-Science-For-Beginners) 80 | * [Data Science Resources](https://github.com/jonathan-bower/DataScienceResources) 81 | * [freeCodeCamp.org's open-source codebase and curriculum](https://github.com/freeCodeCamp/freeCodeCamp) 82 | * [List of Data Science/Big Data Resources](https://github.com/chaconnewu/free-data-science-books) 83 | * [Open Source Society University: Path to a free self-taught Education in Data Science](https://github.com/ossu/data-science) 84 | * [AWESOME DATA SCIENCE: An open-source Data Science repository to learn and apply towards solving real-world problems.](https://github.com/academic/awesome-datascience) 85 | * [Data Science ALL CHEAT SHEET](https://github.com/yash42828/Data-Science--All-Cheat-Sheet) 86 | * [Data Science End-to-End Projects](https://github.com/veb-101/Data-Science-Projects) 87 | * [Data Analysis Projects](https://github.com/arjunmann73/Data-Analytics-Projects) 88 | * [Data Science Interview Resources](https://github.com/rbhatia46/Data-Science-Interview-Resources) 89 | * [Data-Science Interview Questions Answers](https://github.com/youssefHosni/Data-Science-Interview-Questions-Answers) 90 | * [Data-science-best-resources](https://github.com/tirthajyoti/Data-science-best-resources) 91 | * [Amazing-Feature-Engineering](https://github.com/ashishpatel26/Amazing-Feature-Engineering) 92 | * [Complete-Life-Cycle-of-a-Data-Science-Project](https://github.com/achuthasubhash/Complete-Life-Cycle-of-a-Data-Science-Project) 93 | * [Data Science Cheatsheet](https://github.com/ml874/Data-Science-Cheatsheet) 94 | * [PandasAI](https://github.com/gventuri/pandas-ai) 95 | 96 | ## Machine Learning ## 97 | ![alt text](https://github.com/youssefHosni/Awesome-ML-GitHub-Repos/blob/main/images/Machine%20Learning.jpg) 98 | 99 | * [GitHub Community Discussions](https://github.com/community/community): In this repository, you will find categories for various product areas. Feel free to share feedback, discuss topics with other community members, or ask questions. 100 | * [Awesome Machine Learning](https://github.com/josephmisiti/awesome-machine-learning): A curated list of awesome machine learning frameworks, libraries and software (by language). 101 | * [Machine Learning & Deep Learning Tutorials](https://github.com/ujjwalkarn/Machine-Learning-Tutorials): This repository contains a topic-wise curated list of Machine Learning and Deep Learning tutorials, articles and other resources 102 | * [Best-of Machine Learning with Python](https://github.com/ml-tooling/best-of-ml-python): A ranked list of awesome machine learning Python libraries. 103 | * [TensorFlow Examples](https://github.com/aymericdamien/TensorFlow-Examples): This tutorial was designed for easily diving into TensorFlow, through examples. For readability, it includes both notebooks and source codes with explanations, for both TF v1 & v2. 104 | * [Machine Learning Projects](https://github.com/lukas/ml-class) 105 | * [Randy Olson's data analysis and machine learning projects](https://github.com/rhiever/Data-Analysis-and-Machine-Learning-Projects) 106 | * [Minimum Viable Study Plan for Machine Learning Interviews](https://github.com/khangich/machine-learning-interview) 107 | * [Machine Learning Interview Questions: Machine Learning and Computer Vision Engineer](https://github.com/andrewekhalel/MLQuestions) 108 | * [Must Read Machine Learning & Deep Learning Papers](https://github.com/hurshd0/must-read-papers-for-ml) 109 | * [Free Machine Learning Books](https://github.com/shahumar/Free-Machine-Learning-Books) 110 | 111 | ## Machine Learning Projects ## 112 | * [Orca calls Classifier Project](https://github.com/rohankrgupta/Orca-call-Classifier-Machine-learning) 113 | * [Multi-Modal House Price Estimation](https://github.com/Mehrab-Kalantari/Multi-Modal-House-Price-Estimation) 114 | * [Movie Recommendation System Project](https://github.com/Mehrab-Kalantari/Multi-Modal-House-Price-Estimation) 115 | * [Land Cover Semantic Segmentation Project](https://github.com/souvikmajumder26/Land-Cover-Semantic-Segmentation-PyTorch) 116 | * [Music Recommender System using ALS Algorithm with Apache Spark and Python](https://github.com/ramyananth/Music-Recommender-System-using-ALS-Algorithm-with-Apache-Spark-and-Python) 117 | * [Adversarial Task](https://github.com/antonio-f/Adversarial-Task) 118 | * [Flowers Classification](https://github.com/firaja/flowers-classification) 119 | * [99 Machine Learning Projects](https://github.com/gimseng/99-ML-Learning-Projects) 120 | * [Advanced Machine Learning Projects I](https://github.com/beimingliu/AdvancedMachineLearning) 121 | * [Advanced Machine Learning II](https://github.com/mohammadmozafari/advanced-machine-learning) 122 | 123 | ## Machine Learning Engineering Operations (MLOps) ## 124 | ![alt text](https://github.com/youssefHosni/Awesome-ML-GitHub-Repos/blob/main/images/MLOps.png) 125 | * [MLOps Zoomcamp](https://github.com/DataTalksClub/mlops-zoomcamp) 126 | * [MLOps-Basics](https://github.com/graviraja/MLOps-Basics) 127 | * [MLOps Guide](https://mlops-guide.github.io/) 128 | * [Awesome MLOps](https://github.com/visenger/awesome-mlops) 129 | * [Awesome MLOps - Tools](https://github.com/kelvins/awesome-mlops) 130 | * [DTU MLOps](https://github.com/SkafteNicki/dtu_mlops) 131 | * [MLOps Course](https://github.com/GokuMohandas/mlops-course) 132 | 133 | ## Data Engineering ## 134 | ![alt text](https://github.com/youssefHosni/Awesome-ML-GitHub-Repos/blob/main/images/Data%20Engineering.jpg) 135 | 136 | * [Data Engineering Zoomcamp](https://github.com/DataTalksClub/data-engineering-zoomcamp) 137 | * [Data Engineering Cookbook](https://github.com/andkret/Cookbook) 138 | * [How To Become a Data Engineer](https://github.com/adilkhash/Data-Engineering-HowTo) 139 | * [Awesome Data Engineering](https://github.com/igorbarinov/awesome-data-engineering) 140 | * [Data Engineering Roadmap](https://github.com/datastacktv/data-engineer-roadmap) 141 | * [Data Engineering Projects](https://github.com/alanchn31/Data-Engineering-Projects) 142 | * [Data Engineering Interview Questions](https://github.com/OBenner/data-engineering-interview-questions) 143 | 144 | 145 | ## SQL & Database ## 146 | 147 | * [SQL 101 by s-shemmee](https://github.com/s-shemmee/SQL-101) 148 | * [Learn SQL by WebDevSimplified](https://github.com/WebDevSimplified/Learn-SQL) 149 | * [SQL Masterclass by datawithdanny](https://github.com/datawithdanny/sql-masterclass) 150 | * [SQL Map by sqlmapproject](https://github.com/sqlmapproject/sqlmap) 151 | * [SQL Server Samples by Microsoft](https://github.com/microsoft/sql-server-samples) 152 | * [SQL Music Store Analysis Project by Rishabhnmishra]() 153 | * [Data Engineering Zoomcamp by DataTalksClub]() 154 | * [SQL Server Kit by ktaranov]() 155 | * [Awesome DB Tools by mgramin]() 156 | * [SQL for Wary Data Scientists by gvwilson]() 157 | 158 | ## Statistics ## 159 | * [Practical Statistics for Data Scientists](https://github.com/gedeck/practical-statistics-for-data-scientists) 160 | * [Probabilistic Programming and Bayesian Methods for Hackers](https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers) 161 | * [Statsmodels: Statistical Modeling and Econometrics in Python](https://github.com/statsmodels/statsmodels) 162 | * [TensorFlow Probability](https://github.com/tensorflow/probability) 163 | * [The Probability and Statistics Cookbook](https://github.com/mavam/stat-cookbook) 164 | * [Seeing Theory](https://github.com/seeingtheory/Seeing-Theory) 165 | * [Stats Maths with Python](https://github.com/tirthajyoti/Stats-Maths-with-Python) 166 | * [Python for Probability, Statistics, and Machine Learning](https://github.com/unpingco/Python-for-Probability-Statistics-and-Machine-Learning) 167 | * [Probability and Statistics VIP Cheatsheets](https://github.com/shervinea/stanford-cme-106-probability-and-statistics) 168 | * [Basic Mathematics for Machine Learning](https://github.com/hrnbot/Basic-Mathematics-for-Machine-Learning) 169 | 170 | 171 | 172 | 173 | 174 | 175 | 176 | 177 | 178 | --------------------------------------------------------------------------------