Deep Learning

Deep Learning for humans

Caffe: a fast open framework for deep learning.

Deep Learning Book Chinese Translation

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

Foundational deep learning lessons

The most cited deep learning papers

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

The fastai deep learning library, plus lessons and tutorials

PyTorch library aimed at accelerating 3D deep learning research

Geometric Deep Learning Extension Library for PyTorch

A Deep Learning based project for colorizing and restoring old images (and video!)

Deep Learning for humans

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.

DeepFaceLab is the leading software for creating deepfakes.

Visualizer for neural network, deep learning and machine learning models

a distributed deep learning platform

An interactive deep learning book with code, math, and discussions, based on the NumPy interface.

PyTorch Tutorial for Deep Learning Researchers

A Deep-Learning Chess Engine with some awesome features

Machine Learning and Deep Learning lessons.

Find implementation of Computer vision based projects with Python, Deep Learning and OpenCV

DeepLearning Models using Keras framework

This repository is for contributing good quality study materials for learning TensorFlow for beginners from the basics to the intermediate or to an advanced level. Anyone can contribute your knowledge in this field, which can help the people who are interested in learning TensorFlow.

Natural language processing (NLP) is an exciting branch of artificial intelligence (AI) that allows machines to break down and understand human language. I plan to walk through text pre-processing techniques, machine learning techniques and Python libraries for NLP. Text pre-processing techniques include tokenization, text normalization and data cleaning. Once in a standard format, various machine learning techniques can be applied to better understand the data. This includes using popular modeling techniques to classify emails as spam or not, or to score the sentiment of a tweet on Twitter. Newer, more complex techniques can also be used such as topic modeling, word embeddings or text generation with deep learning. We will walk through an example in Jupyter Notebook that goes through all of the steps of a text analysis project, using several NLP libraries in Python including NLTK, TextBlob, spaCy and gensim along with the standard machine learning libraries including pandas and scikit-learn.

An interactive deep learning book with code, math, and discussions, based on the NumPy interface.

Deep Learning for Visual Tracking: A Comprehensive Survey

The wonderful and illustrative notes on Deep Learning take will take a person from Zero to Hero.

Music Generation using Deep Learning in Python with Tensorflow & Keras

Deep Learning Class

Deep Learning under Privileged Information Using Heteroscedastic Dropout (CVPR 2018, Official Repo)

Implementations of the Deep Q-Learning Algorithms for Auctions

Bản dịch cuốn sách "Dive into Deep Learning"

Trax — Deep Learning with Clear Code and Speed

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

Explainability of Deep Learning Models

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

Materials for the Deep Learning -- ÚFAL course NPFL114

Repository for scripts and notebooks from the book: Beginner’s Guide to Using PyTorchfor Deep Learning

Serve machine learning models within a Docker container using Amazon SageMaker.

Geometric Deep Learning Extension Library for PyTorch

A library for encrypted, privacy preserving machine learning

A deep learning package for many-body potential energy representation and molecular dynamics

Federated Deep Learning in PaddlePaddle

Visualizer for neural network, deep learning and machine learning models

Deep Learning Models optimized for AWS

Markerless pose estimation of user-defined features with deep learning for all animals

Deep Learning Library for Single Cell Analysis

A deep learning framework for multi-animal pose tracking.