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.

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.

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

The fastai deep learning library, plus lessons and tutorials

PyTorch library aimed at accelerating 3D deep learning research

Books for machine learning, deep learning, math, NLP, CV, RL, etc

DeepFaceLab is the leading software for creating deepfakes.

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

Simple Distributed Deep Learning on TensorFlow

Visualizer for neural network, deep learning and machine learning models

Paddle.js is an Web project for Baidu Paddle, which is an an open source deep learning framework designed to work on web browser. Load a pretrained paddle.js SavedModel or Paddle Hub module into the browser and run inference through Paddle.js. It could run on nearly every browser with WebGL support.

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.

Fawkes, privacy preserving tool against facial recognition systems. More info at http://sandlab.cs.uchicago.edu/fawkes

Fully automated machine learning in one-liners.

A Deep-Learning Chess Engine with some awesome features

Machine Learning and Deep Learning lessons.

DeepLearning Models using Keras framework

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.

COVID-19: Face Mask Detector with OpenCV, Keras/TensorFlow, and Deep Learning

Developed using Pybullet, OpenCV and Deep Learning

Earthquake Responses prediction using Deep learning and Database

My Notes & Templates on Deep Learning/Apache Spark; Used for building code faster

Collection of papers in machine learning, deep learning and neuroscience

ZeroCostDL4Mic: A Google Colab based no-cost toolbox to explore Deep-Learning in Microscopy

An Open-Source Library for Training Binarized Neural Networks

Deep Learning (with PyTorch)

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference

ImJoy: Deep Learning Made Easy!

Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals

AutoML library for deep learning

Tutorials for deep learning course here:

Elastic Deep Learning using PaddlePaddle and Kubernetes

The first deep learning based Nanopore simulator which can simulate the process of Nanopore sequencing.

OpenVINO Toolkit repository

AutoML library for deep learning

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference

A small library for managing deep learning models, hyperparameters and datasets

Elastic Deep Learning using PaddlePaddle and Kubernetes

️ Generate photo-realistic textures based on source images. Remix, remake, mashup! Useful if you want to create variations on a theme or elaborate on an existing texture.

ktrain is a Python library that makes deep learning and AI more accessible and easier to apply

Combining Deep RL and SimPy models of hospital systems

This repository allows you to get started with training a state-of-the-art Deep Learning model with little to no configuration needed! You provide your labeled dataset or label your dataset using our BMW-LabelTool-Lite and you can start the training right away and monitor it in many different ways like TensorBoard or a custom REST API and GUI. Training with YOLOv4 and YOLOV3 has never been so easy.

DELTA is a deep learning based natural language and speech processing platform.

Simple Distributed Deep Learning on TensorFlow