Misha Brukman's Projects
The Deadlock Empire: Slay dragons, learn concurrency!
Julia debugger
Declarative Shadow DOM feature development
Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
deep learning for image processing including classification and object-detection etc.
Introduction to Deep Neural Networks with Keras and Tensorflow
:satellite: All You Need to Know About Deep Learning - A kick-starter
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Repo for the Deep Reinforcement Learning Nanodegree program
Deep neural networks for voice conversion (voice style transfer) in Tensorflow
Course notes
Analyze Data with Pandas-based Networks. Documentation:
Deep learning driven jazz generation using Keras & Theano!
DeepLab2 is a TensorFlow library for deep labeling, aiming to provide a unified and state-of-the-art TensorFlow codebase for dense pixel labeling tasks.
Topics on theoretical, mathematical aspects of DL
A collection of various deep learning architectures, models, and tips
Deep Learning for Java, Scala & Clojure on Hadoop, Spark & GPUs
MIT Deep Learning Book in PDF format
Deep Learning Examples
Deep Learning Tutorial notes and code. See the wiki for more info.
TensorFlow Basic Tutorial Labs
Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.
Open source code for AlphaFold.
Lua/Torch implementation of DQN (Nature, 2015)
A customisable 3D platform for agent-based AI research
This repository contains implementations and illustrative code to accompany DeepMind publications
Implementation of some deep learning algorithms.