Practical machine learning notebook & articles covers the machine learning end to end life cycle.

Get data from API, run a scheduled script with Airflow, send data to Kafka and consume with Spark, then write to Cassandra

VIP cheatsheets for Stanford's CS 230 Deep Learning

A Configurable Recommender Systems Simulation Platform

🏆 A ranked gallery of awesome streamlit apps built by the community

Pytorch implementation of U-Net, R2U-Net, Attention U-Net, and Attention R2U-Net.

Visually simulate Git operations in your own repos with a single terminal command.

Experiments with U-net architectures on image auto encoding tasks

A curated list of data science educational resources for essential data science skills

Multi-Agent Reinforcement Learning (MARL) papers with code

Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch

🧮 A collection of resources to learn mathematics for machine learning

OpenAi's gym environment wrapper to vectorize them with Ray

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyp…

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Rainbow is all you need! A step-by-step tutorial from DQN to Rainbow

Collection of scripts used in my Medium articles.

Awesome free machine learning and AI courses with video lectures.