Stars
This repo contains the Hugging Face Deep Reinforcement Learning Course.
📺 Discover the latest machine learning / AI courses on YouTube.
🎓 Sharing machine learning course / lecture notes.
Learn how to develop, deploy and iterate on production-grade ML applications.
Learn how to design, develop, deploy and iterate on production-grade ML applications.
Free ways to dive into machine learning with Python and Jupyter Notebook. Notebooks, courses, and other links. (First posted in 2016.)
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
A topic-centric list of HQ open datasets.
An advanced program in Machine Learning and Deep Learning
A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and code
Modern JavaScript Tutorial
Data science interview questions and answers
Dedicated Resources for the Low-Level System Design. Learn how to design and implement large-scale systems. Prep for the system design interview.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Awesome free machine learning and AI courses with video lectures.
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
STAT 453: Intro to Deep Learning @ UW-Madison (Spring 2020)
Open Deep Learning and Reinforcement Learning lectures from top Universities like Stanford, MIT, UC Berkeley.
Distributed Asynchronous Hyperparameter Optimization in Python
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
A game theoretic approach to explain the output of any machine learning model.
Book about interpretable machine learning
Course material for STAT 479: Machine Learning (FS 2018) at University Wisconsin-Madison
Course material for STAT 479: Deep Learning (SS 2019) at University Wisconsin-Madison
A collection of various deep learning architectures, models, and tips