Table Of Contents
- Some of the Best Github Repos and Open Source Machine Learning Projects (Our Favorite from the List)
- Awesome Machine Learning
- Machine Learning for Beginners (A Curriculum)
- ML Glossary
- Homemade Machine Learning
- ML Residency
- Machine Learning Pipeline
- Machine Learning Courses On YouTube
- Machine Learning Notes
- Machine Learning for Software Engineers
- Applied Machine Learning
- Papers Reading Roadmap
- Machine Learning Interviews
- Production Machine Learning
- Interactive Tools
- Foundation Of ML
- Best of Machine Learning with Python
- Practical Reinforcement Learning
- Machine Learning Projects And Tutorials
- Deep Learning For Music
- ML Surveys
- Paper Code Interpretation
- Deep Learning In Production
- Deep Learning Paper Implementations
- Public Datasets
- Awesome TensorFlow
- Deep Learning Drizzle
- Machine Learning on Source Code
- Autonomous Vehicles
- GANs Applications & Demonstrations
- Computer Vision
- Awesome NLP
- Have Fun with Machine Learning
- Production Deep Learning
- Awesome Reinforcement Learning
- Machine Learning Cheat Sheets
- Deep Learning Papers
- Machine learning Basics
- Machine Learning Videos
- Awesome Youtubers
- Machine Learning Tutorials
- Awesome Deep Learning
- Speech and Natural Language Processing
- Machine Learning with Python
- 3D Machine Learning
- Machine Learning Applications in Industry
- Machine Learning Mindmap
- Python Machine Learning Jupyter Notebooks
- Financial Machine Learning and Data Science
- Machine Learning Interpretability
- Bayesian Machine Learning Notebooks
- State-of-the-art result for all Machine Learning Problems
- Machine Learning for Cyber Security
- Awesome Artificial Intelligence
- Start Machine Learning in 2022
- Machine Learning Surveys
- Machine Learning From Scratch
- System for ML
- Quant Machine Learning Trading
- ML for Cyber Security
- Machine Learning Algorithms
- Stock Prediction Models
- Deep Learning Projects
- Deep Vision
- Deep Learning Project Ideas
- Multimodal ML
- TensorFlow without a PHD
- Machine Learning With Ruby
- Graph-based Deep Learning
- Image Classification
- Deep Learning Papers By Task
- Deep Learning For Tracking & Detection
- Graph Deep Learning
- Awesome Python
- Reinforcement Learning
- NLP Overview
- Text Summarization
- Community Detection
- Knowledge Graphs
- NLP & Machine Learning Surveys
- Style Transfer In Text
- Awesome Pytorch
- Textual Adversarial Attack and Defense
- NLP Tasks
- Courses And Video Lectures
- 3D Reconstruction
- Human Pose Estimation
- Pretrained Models
- Text Detection and Recognition
- Image To Image
- Capsule Networks
- Synthetic Computer Vision
- Neural Rendering
- TensorFlow 2.x Tutorials
- Data Augmentation
- Time Series in Python
- Anomaly Detection
- Deep / Algorithmic Trading
- Action Recognition
- Object Detection
- Pattern Classification
- Satellite Imagery
- Effective TensorFlow 2
- TensorFlow Tutorials
- Adversarial Nets Papers
- Paper Summaries
- Deep Learning.AI Course Summary
- Deep Learning Roadmap
- Self Supervised Learning
- NLP Best Practices
- Face Recognition
- Open Source Projects
- Recommender System
- Visual Tracking Papers
- Computational Advertising Papers
- 60 Days Of Deep Reinforcement Learning
- Machine Learning Papers Summaries
- Tracking & Detection
- DeepLearn Implementation
- ML Notebooks
- 100 Days of Machine Learning Challenge
- Awesome AWS
- Deep Learning Research Papers
- Core ML Models
- Useful Java Links
- The GAN Zoo
- Decision Tree Research Papers
- PyTorch Image Models
- Machine Learning in Asset Management
- From Zero to Research Scientist Full Resources Guide
- Machine Learning Interviews
- Deep Learning For Graphs
- Machine Learning Tutorials
- TensorFlow Examples
- Quantum Machine Learning
Rapid Fire Question: If anyone had to pick one platform that can single-handedly keep you up-to-date with the latest developments in data science and machine learning, what would be your answer? Some of you might say Kaggle, Twitter, StackOverflow, Quora, Discord or something else. But the majority of you will say Reddit or GitHub. So, To help you by sharing everything in one place, We’re here with a curated list of 100+ widely-known as well as lesser-known repositories and open source github projects for Machine Learning and Deep Learning. Let’s see all the hubs created by experts as well as big organizations.
Some of the Best Github Repos and Open Source Machine Learning Projects (Our Favorite from the List)
- Machine Learning for Beginners
- Machine Learning Interviews From FAANG
- Latest Free Machine learning Courses (On YouTube)
- Machine Learning with Python
- 880 Awesome Open-Source Machine Learning Projects
- Machine Learning Cheat Sheets
- Awesome TensorFlow and Reinforcement Learning
- Machine Learning Algorithms in Python
- Best Free Resources To Learn Machine Learning
In this repo, You’ll get a curated list of awesome Machine Learning frameworks, libraries and software.
Microsoft has created a free MIT-approved learning course titled “Machine Learning For Beginners” to teach students the basics of machine learning. The curriculum covers: What techniques do ML researchers use to build Machine Learning Models, How to build linear and polynomial regression models, How to build a web app to use your trained model, What are the real-world applications of classical Machine learning and a lot more. This is one of the best github repositories and open source machine learning projects for beginners and even intermediates.
Brief visual explanations of machine learning concepts with diagrams, code examples and links to resources for learning more. The goal of the glossary is to present content in the most accessible way possible, with a heavy emphasis on visuals and interactive diagrams.
This github repos covers python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained.
In this github repo, You’ll find curated AI and ML Residency Programs from top companies like Apple, Microsoft, Google, NVIDIA, Intel and more.
An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch. This tutorial tries to do what most Most Machine Learning tutorials available online do not. It is not a 30 minute tutorial which teaches you how to “Train your own neural network” or “Learn deep learning in under 30 minutes”.
This repository index and organize the latest machine learning courses found on YouTube. If you’re a beginner then you must check this repo once before you move on to other articles or below given list. This is the one of the best github repositories & open source machine learning projects with summaries related to all the ML courses.
It contains continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides). Topics covered in this notes are Neural Networks Gaussian Process and Neural Tangent Kernel Initialization, Inference, Regression methods, Recommendation system, Word Embeddings, Deep Natural Language Processing, Conjugate Gradient Descend, Lagrangian Dual, Monto Carlo Tree Search, Policy Gradient, Advanced Probabilistic Model, Restricted Boltzmann Machine, Advanced Variational Autoencoder, 3D Geometry Fundamentals and more.
An approach to studying Machine Learning that is mainly hands-on and abstracts most of the Math for the beginner. This approach is unconventional because it’s the top-down and results-first approach designed for software engineers.
Papers & tech blogs by companies sharing their work on data science & machine learning in production.
If you are a newcomer to the Deep Learning area, the first question you may have is “Which paper should I start reading from?” Check out the reading roadmap of Deep Learning papers given in this repo!
Machine Learning Interviews from FAAG, Snapchat, LinkedIn. The author has created this repo on the basis of his personal experience.
This repository contains a curated list of awesome open source libraries that will help you deploy, monitor, version, scale, and secure your production machine learning.
This is one of the best and most recommended github repo for all machine learning practitioners. You will find interactive and visualization tools that will help you understand Bert, Convolution Neural Network, GANs, Probability, Statistics and other topics of deep learning and machine learning.
Using this repo, You can learn the foundations of ML through intuitive explanations, clean code and visuals. Also, You can learn how to apply ML to build a production grade product to deliver value.
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This curated list contains 880 awesome open-source projects on Data Visualization, NLP, Time Series, Distributed Machine Learning, Data Pipelines & Streaming, Hyperparameter Optimization & AutoML, Model Interpretability, Reinforcement Learning, Recommender Systems and other topics. This is considered as one of the best github repositories and open source machine learning projects for beginners, intermediate and advanced ML enthusiasts.
In this repository, You’ll find an open course on reinforcement learning in the wild. This course has been already taught on-campus at HSE and YSDA and maintained to be friendly to online students.
Expert’s Curated Blogs, Articles, Videos, Papers, Codes, Books, Talks, Newsletters and more on Machine Learning Operations.
In this repository you will find tutorials and projects related to Machine Learning. The author has tried to make the code as clear as possible, and the goal is be to used as a learning resource and a way to lookup problems to solve specific problems.
A list of summer schools in machine learning & related fields across the globe.
Non-exhaustive list of scientific articles, thesis and reports on deep learning for music.
Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
Collection of Cvpr2021, Cvpr2020, Cvpr2019, Cvpr2018 and Cvpr2017 thesis/code/interpretation/live broadcast, papers and projects.
In this repository, You’ll find some useful notes and references about deploying deep learning-based models in production.
A collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations and side-by-side notes.
A topic-centric list of high quality open datasets for Machine Learning, Time Series, NLP, Image Processing and more.
A curated list of awesome TensorFlow Tutorials, Models/Projects, Libraries, Tools/Utilities, Videos, Papers, Articles, Community, Books and more.
Drench yourself in Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!
A curated list of awesome research papers, software projects devoted to ML and source code.
Courses, Papers, Research Labs, Datasets, Open Source Software, Hardware, Toys, Companies, Media and Laws related to Autonomous Vehicles.
A curated list of awesome GAN tutorials, applications, projects, research papers and demos.
Awesome Papers, Software, Datasets, Pre-trained Computer Vision Models, Tutorials, Talks, Blogs, Links and Songs related to Computer Vision.
This repository has a collection of best tutorials, projects, libraries, papers, and anything related to the incredible PyTorch.
A curated list of Research Summaries and Trends, Prominent NLP Research Labs, Reading Content, Videos and Courses, Books, Libraries, Datasets and Annotation Tools dedicated to Natural Language Processing (NLP).
An absolute beginner’s guide to Machine Learning and Image Classification with Neural Networks. A hands-on guide to machine learning for programmers with no background in AI.
A guideline for building practical production-level deep learning systems to be deployed in real world applications.
A handpicked collection of Lectures, Books, Surveys, Papers / Thesis, Codes, Tutorials / Websites, Online Demos and Open Source Reinforcement Learning Platforms related to Reinforcement Learning.
This repository aims at summing up in the same place all the important notions that are covered in Stanford’s CS Machine Learning course, and include: Refreshers in related topics that highlight the key points of the prerequisites of the course and Cheatsheets for each machine learning field, as well as another dedicated to tips and tricks to have in mind when training a model. In this list, is considered as one of the best free machine learning resource and github repositories for beginners.
This repo covers the most cited papers on various topics like Image Segmentation / Object Detection, Natural Language Processing / RNNs, Reinforcement Learning / Robotics, and more.
This repository contains implementations of basic machine learning algorithms in plain Python (Python Version). All algorithms are implemented from scratch without using additional machine learning libraries. The intention of these notebooks is to provide a basic understanding of the algorithms and their underlying structure, not to provide the most efficient implementations.
This is a collection of amazing recorded talks at machine learning conferences, workshops, seminars, summer schools, and miscellaneous programs.
An awesome list of awesome YouTubers that teach about technology.
This repository contains a topic-wise curated list of Deep Learning tutorials, articles and other resources.
A curated list of awesome Deep Learning tutorials, video lectures, research papers, blogs, datasets, frameworks, researchers, conferences, tools, projects, free books pdf, and communities.
A curated list of speech and natural language processing resources. It includes Finite State Toolkits and Regular Expressions, Language Modelling Toolkits, Speech Recognition Tools, Signal Processing Tools, Machine Translation Tools, Blogs, Books and more.
- Are You Looking For Interesting, Mini And Innovative Machine Learning Projects With Source Code? If Yes, Then You Must Check Out This List: 30 Innovative Machine Learning Projects For Beginners With Source Code
- Cool Machine Learning Applications: How Big Companies Like Quora, Twitter, eBay, Snapchat, Uber And Netflix Solves Real-World Problems Using Machine Learning
This Repository contains python codes for essential and common machine learning algorithms like Random Forest, Linear Regressions, Support Vector Machines, Naive Bayes Classifier, Principal Component Analysis, Logistic Regression, Decision Trees, XgBoost, Clustering and more. This repo is considered as one of the best github repositories and open source machine learning projects for ML practitioners.
It covers Courses, Datasets for D Models, Research Papers for D Pose Estimation, Single Object Classification, Multiple Objects Detection, Scene/Object Semantic Segmentation, D Geometry Synthesis / Reconstruction, Parametric Morphable Model-based methods, Part-based Template Learning methods, Texture/Material Analysis and Synthesis, and more.
A comprehensive updated list of Artificial Intelligence, Machine Learning & Deep Learning Tutorials. In addition, You will also find deep learning blogs along with rss links.
A curated list of applied machine learning and data science notebooks and libraries across different industries.
A Mindmap summarizing Machine Learning concepts, from Data Analysis to Deep Learning.
Practice and tutorial-style notebooks covering wide variety of machine learning techniques. Jupyter notebooks covers a wide range of functions and operations on the topics of NumPy, Pandas, Seaborn, Matplotlib etc. Tutorial-type notebooks covers regression, classification, clustering, dimensionality reduction, and some basic neural network algorithms.
A curated list of practical financial machine learning tools and applications. This collection is primarily in Python.
A curated list of awesome machine learning interpretability resources. Resources includes Comprehensive Software Examples and Tutorials, Government and Regulatory Documents, Review and General Paper, Classes and more.
This repository is a collection of notebooks about Bayesian Machine Learning.
This repository provides state-of-the-art (SoTA) results for all machine learning problems.
A handpicked list of tools and resources related to the use of machine learning for cyber security.
A curated list of Artificial Intelligence courses, books, video lectures, competitions, AI newsletters, Free books, and papers.
A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in without any background in the field and stay up-to-date with the latest news and state-of-the-art techniques!
A huge list of Artificial Intelligence, Deep learning, Computer vision, NLP and Machine learning Projects with source code.
A curated list of Surveys, Tutorials and Books on Active Learning, Bioinformatics, Multi-Armed Bandit, Transfer Learning, etc.
Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. It aims to cover everything from linear regression to deep learning.
A curated list of research in machine learning system. In this repo, You’ll also find the summary of some of the most interesting research papers.
Quant/Algorithm trading resources with an emphasis on Machine Learning. Resources covered by the machine learning research engineer includes youtube videos, blogs and articles, interviews, research papers, codes and more
A curated list of awesome resources related to the use of machine learning for cyber security.
A collection of minimal and clean implementations of machine learning algorithms. This repo is targeting people who want to learn internals of ml algorithms or implement them from scratch.
A helpful list of machine learning and deep learning models for Stock forecasting.
In this repo, There are specific bite-sized projects to learn an aspect of deep learning from scratch. The projects are in order from beginner to more advanced, but feel free to skip around.
Simple Implementation of machine learning and deep learning models. The original implementations are quite complex and not really beginner friendly. The author has created this repo to break that complexity and tried to simplify most of it.
A curated list of deep learning Papers, Courses, Books, Videos, Tutorials, Blogs and Softwares for computer vision.
A Handpicked collection of 30+ Natural Language Processing, Recommender Systems, Deep Learning and Machine Learning Project Ideas.
Research Papers for Multimodal Machine learning. Apart from papers, You’ll also find Datasets, Workshops, Tutorials and Courses on Multimodal ML.
A crash course in six episodes for software developers who want to learn machine learning, with examples, theoretical concepts, and engineering tips, tricks and best practices to build and train the neural networks that solve your problems. In this list, is considered as one of the best github repositories and open source machine learning projects.
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A curated list comprises of data sources, tutorials and presentations for Machine Learning.
The repository contains links primarily to conference publications in graph-based deep learning.
A curated list of top deep learning image classification papers and codes.
Papers about deep learning ordered by task, date. Current state-of-the-art papers are labelled.
You’ll find papers, datasets, code and other resources for object tracking and detection using deep learning.
A comprehensive collection of recent papers on deep learning for graphs.
A curated list of awesome Python frameworks, libraries, software and resources.
A list of 100+ project based OpenCV articles and their codes.
This repository contains Artificial Intelligence Roadmap, Machine Learning Roadmap, Deep Learning Roadmap, Big Data Roadmap and Data Science Roadmap.
A collection of image annotation, video annotation, semantic segmentation and data labelling tools.
A series of simple Reinforcement Learning Methods and Tutorials covering basic RL Algorithms to recently updated advanced algorithms.
This github repos contains an overview of recent trends in deep learning based natural language processing (NLP). It covers the theoretical descriptions and implementation details behind deep learning models, such as recurrent neural networks (RNNs), convolutional neural networks (CNNs), and reinforcement learning, used to solve various NLP tasks and applications.
A curated list of resources dedicated to text summarization.
A curated list of community detection research papers with implementations.
A curated list of automated deep learning (including neural architecture search and hyper-parameter optimization) resources.
A collection of Softwares, Tools, Courses, Tutorials, Seminars, Related Github Repos, Research Papers and more on Knowledge Graphs.
A collection of 700+ survey papers on Natural Language Processing (NLP) and Machine Learning (ML)
This is a paper list for style transfer in text. It also contains some related research areas, including controlled text generation.
A comprehensive list of pytorch related content on github, such as different models, research paper implementations, tutorials etc.
A collection of must-read papers on Textual Adversarial Attack and Defense.
A Handpicked list of Natural Language Processing Tasks, Projects, Papers, Challenges and Selected References.
A Huge Collection of free Image Processing, Computer Vision, Artificial Intelligence and Machine Learning related courses and video lectures.
A curated list of papers & resources linked to D reconstruction from images.
If you want to learn the basics of Human Pose Estimation and understand how the field has evolved, check out this repo filled with curated papers and free resources.
A collection of 100+ computer vision pre-trained models.
A curated list of resources for text detection/recognition (optical character recognition) with deep learning methods.
A collection of image-to-image papers. Papers are ordered in arXiv first version submitting time (if applicable).
A List of Videos, Blogs, Papers with Source Code and Implementations, and other resources related to capsule networks.
A list of synthetic dataset and tools for computer vision. This is a repo for tracking the progress of using synthetic images for computer vision research.
A collection of papers, implementations and other resources on neural rendering.
TensorFlow 2.x version’s Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc.
In this repo, You’ll find a curated list of useful data augmentation resources. You will also find here some not common techniques, libraries, links to github repos, papers and others.
This repo contains a list of popular python packages for time series analysis
A curated list of awesome anomaly detection papers and their source code.
This repo has a curated list of automated machine learning papers, articles, tutorials, slides and projects.
A collection of code, papers, and resources for AI/deep learning/machine learning/neural networks applied to algorithmic trading.
A curated list of Action Recognition, Action Classification, Object Recognition and Pose Estimation Resources.
In this repo, You’ll find a list of awesome articles about object detection. If you want to read the paper according to time, you can refer to Date.
A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks.
This repository explores different machine learning techniques people are applying to common problems in satellite imagery analysis.
In this repo, You’ll find best Practices and Tutorials on TensorFlow .
A collection of updated tutorials for TensorFlow . This repository is intended for those who are beginning their journey in Deep Learning and Tensorflow.
You will find awesome papers about Generative Adversarial Networks. The majority of papers are related to Image Translation, Facial Attribute Manipulation, Generative Models, Image Inpainting, GAN Theory and more.
This repository contains a list of NLP paper summaries intended to make NLP techniques approachable and accessible. The contributors and authors have identified and listed several important papers with summaries in this repository. In this list, this is considered as one of the best github repositories and open source machine learning projects.
This repository contains author’s personal notes and summaries on DeepLearning.ai specialization courses.
The author has created a deep learning roadmap for all the beginners. This roadmap repository contains a collection of resources like tutorials, free courses, blogs, papers and a lot more.
In this repo, You’ll find a collection of pre-trained, state-of-the-art machine learning models in the ONNX format.
A curated list of awesome self-supervised learning Graphs, Talks, Thesis, Blogs, surveys, papers and a lot more.
This repository contains examples / best practices for building NLP systems, provided as Jupyter notebooks and utility functions.
In this repo, You’ll find papers about Face Detection, Face Alignment, Face Recognition, Face Reconstruction, Face Tracking, Face Super-Resolution, Face Generation, Face Transfer, Face Anti-Spoofing and Face Retrieval
This repo contains popular github projects related to deep learning are provided and rated according to stars.
This repository provides a curated list of papers about Recommender Systems including comprehensive surveys, general recommender system, social recommender system, exploration and exploitation problem in recommender system and more.
In this repo, You’ll find a mindmap of deep learning and visual tracking papers.
A collection of computing advertising-related papers and learning materials that have been implemented or read in the work and share with the industry, as a summary of their own work, and hope to bring convenience to students in computing advertising-related industries.
Learn Beginners, Intermediate and Advanced Deep Reinforcement Learning topics in days! In this repo, You’ll find everything well arranged from articles, tutorials, youtube videos, papers implementations, projects and codes.
Short summaries of some of the best machine learning papers.
A collection of papers, datasets, code and other resources for object tracking and detection using deep learning.
This repository contains implementation of some popular research papers on NLP, ML, and Deep Learning.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning in python using Scikit-Learn.
A machine learning challenge repo with insightful infographics, tutorials, codes and more. Take this challenge and start diving into machine learning coding.
A curated list of awesome Amazon Web Services (AWS) libraries, open source repos, guides, blogs, and other resources. Featuring the Fiery Meter of AWSome.
A list of recent papers regarding deep learning and deep reinforcement learning. They are sorted by time to see the recent papers first.
The largest collection of machine learning models in Core ML format, to help iOS, macOS, tvOS, and watchOS developers experiment with machine learning techniques.
A list of useful Java tools, frameworks, libraries and hello worlds examples for Machine learning Practitioners.
Every week, new GAN papers are coming out and it’s hard to keep track of them all, not to mention the incredibly creative ways in which researchers are naming these GANs! So, In this repo, You’ll find a list of what started as a fun activity compiling all named GANs!
A collection of research papers on decision, classification and regression trees with implementations.
PyTorch image models, scripts, pretrained weights — ResNet, ResNeXT, EfficientNet, EfficientNetV, NFNet, Vision Transformer, MixNet, MobileNet-V/V, RegNet, DPN, CSPNet, and more.
In this repo, You’ll find a curated list of robotics libraries and simulators.
A small list of 25+ research papers for Machine Learning in Asset Management.
This guide is designated to anybody with basic programming knowledge or a computer science background interested in becoming a Research Scientist with target on Deep Learning and NLP.
This repo aims to be an enlightening guideline to prepare for Machine Learning / AI technical interviews. It has compiled based on the personal experience and notes from author’s own ML interview preparation early , when he received offers from Facebook (ML Specialist), Google (ML Engineer), Amazon (Applied Scientist), Apple (Applied Scientist), and Roku.
A comprehensive collection of recent papers on graph deep learning.
A collection of + machine learning tutorials mostly written in python. The content aims to strike a good balance between mathematical notations, educational implementation from scratch using Python’s scientific stack including numpy, numba, scipy, pandas, matplotlib, etc. and open-source library usage such as scikit-learn, pyspark, gensim, keras, pytorch, tensorflow, etc. In this list, this is considered as one of the best github repositories and open source machine learning projects.
TensorFlow Tutorial and Examples for Beginners. This tutorial was designed for easily diving into TensorFlow, through examples.
In this repo, You will find resources related to Quantum Machine Learning Basics, Quantum Machine Learning Algorithms, Quantum Neural Networks, Quantum Statistical Data Analysis, Quantum Artificial Intelligence, Quantum Computer Vision and more.
GitHub repositories are like casinos with valuable resources that can kickstart your Machine Learning journey. With the plenty of free resources above, you are well-equipped to learn about Machine learning, Deep Learning and Artificial Intelligence with your very own curriculum. Wait, Bookmark this post as you may forgot this list or even this website. One more thing, If you think we’ve missed any best repository or github project for machine learning or deep learning, you can share it with us on any of our social media accounts.