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Public material for CS109
A curated list of awesome imitation learning resources and publications
A curated list of resources for Learning with Noisy Labels
A curated list of awesome self-supervised methods
Code implementation of the paper "Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks", at IEEE Security and Privacy 2019.
Course materials/Homework materials for the FREE MOOC course on "Creative Applications of Deep Learning w/ Tensorflow" #CADL
Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch
Conditional RNNs made easy with Tensorflow and Keras.
Interactive deep learning book with code, math, and discussions. Available in multi-frameworks.
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
Deep Learning Illustrated (2020)
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Deeplearning4j Examples (DL4J, DL4J Spark, DataVec)
Deep Learning with TensorFlow, Keras, and PyTorch
Duke-Tsinghua Machine Learning Summer School 2017
The fastai book, published as Jupyter Notebooks
Solve finite Markov Decision Process models.
starter from "How to Train a GAN?" at NIPS2016
Generative Adversarial Networks implemented in PyTorch and Tensorflow
An introduction to git.
Course materials for Georgia Tech CS 4650 and 7650, "Natural Language"
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Lab Materials for MIT 6.S191: Introduction to Deep Learning
Visualizing RNNs using the attention mechanism
Attention mechanism Implementation for Keras.
The project uses Keras on top of a Tensorflow LSTM to predict bearings, latitude/longitude, delays, and speeds for Metlink bus ping data
This repository is to prepare for Machine Learning interviews.
A collection of machine learning examples and tutorials.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.