Feel free to fork this repo and check off the items as you wish. If you want help forking the repo see blah. To contribute, please pull out an issue.
- What technology is “cutting edge” in 2022?
- Difference between AI and Machine Learning
- Machine Learning + | Machine Learning
- How To Create A Successful Artificial Intelligence Strategy
- Ethics in AI
- How To Create A Successful Artificial Intelligence Strategy
- MIT AI Blog
- HBR on AI
- Great Learning Blog
- Visualizing K-Means Clustering
- An A.I.-Generated Picture Won an Art Prize. Artists Aren’t Happy.
- Jeff Dean: AI isn't as smart as you think -- but it could be | TED
- Explainable AI for Software Engineering
- How to build recommendation algorithms and system designs
- Emerging Architectures for Modern Data Infrastructure
- Chess Engines: A Zero to One
- Introduction to streaming for data scientists
- Linear Models
- AI for the Next Era
- Illustrated Stable Diffusion
- Deep Mind Blog
- A Deep Learning Approach to Antibiotic Discovery
- Self Parking Cars in 500 Lines of Code
- Line art Repo
- An A.I.-Generated Picture Won an Art Prize. Artists Aren’t Happy.
- Chess Engine
- Stock prediction AI
- Top 47 Machine Learning Projects for 2022 [Source Code Included]
- Automatic Youtube subtitle generation
- Hugging Face
- Machine Learning Mastery - get started
- Machine Learning from Scratch
- Data Engineering Cookbook
- Deep Learning in Production
- Machine Learning in Production — Table of Contents
- How to put machine learning models into production
- MLOPs Primer
- Dev Ops Roadmap 2022
- DevSecOps
- Rosalind
- bioinformaticsdotca
- Welcome to the RNA-seq Bioinformatics Course.
- bioinformatics.org
- Biostars
- Hypergraph-based connectivity measures for signaling pathway topologies
- monai.io
- Machine Learning for Beginners - A Curriculum | Microsoft
- Dive into Machine Learning
- Practical Deep Learning
- Machine Learning with Python
- Your First Deep Learning Project in Python with Keras Step-by-Step
- MIT Courses
- AI for Trading
- Eat TensorFlow2 in 30 days
- A demo of K-Means clustering on the handwritten digits data
- MLExpert
- SEC595: Applied Data Science and Machine Learning for Cybersecurity Professionals
- Scikit learn
- Pandas
- MATLAB
- Tensorflow
- Keras
- Pytorch
- Sematic - An open-source ML pipeline development toolkit
- igel - delightful machine learning tool that allows you to train, test, and use models without writing code.
- OCaml - is a general-purpose, industrial-strength programming language with an emphasis on expressiveness and safety.
- NetworkX - NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
- Kedro - is an open-source Python framework for creating reproducible, maintainable and modular data science code.
- Project Lightspeed - A self contained OBS -> FTL -> WebRTC live streaming server.
- Scalable ML Pipelines - open-source library that simplifies the creation of massively scalable machine learning (ML) pipelines.
- Federated Learning Framework - is a framework for building federated learning systems.
- AI template - AITemplate is a Python framework which renders neural network into high performance CUDA/HIP C++ code.
Many Thanks to TLDR and all the contributions from other sources