11 Jul 2018views: 4
Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence. Deep learning is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms. Learning can be supervised, semi-supervised or unsupervised.
The "deep" in "deep learning" refers to the number of layers through which the data is transformed. Deep learning models are inspired by information processing and communication patterns in biological nervous systems yet have various differences from the structural and functional properties of biological brains.
Deep Learning is a vast field and cannot be understood without proper time investment into the field as one have to learn many theory maths and algorithms. The true power of Deep Learning lies in the Learning or Training process. To get started here is the top frameworks and projects regarding Deep Learning on GitHub.
Here's a list of top 180 deep learning Github repositories sorted by the number of stars and popularity.
Computation using data flow graphs for scalable machine learning. TensorFlow is an open source software library for numerical computation using data flow graphs. The graph nodes represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture enables you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device without rewriting code.
Deep Learning for humans. Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research.
Open Source Computer Vision Library. OpenCV (Open Source Computer Vision Library) is released under a BSD license and hence it’s free for both academic and commercial use. It has C++, Python and Java interfaces and supports Windows, Linux, Mac OS, iOS and Android. OpenCV was designed for computational efficiency and with a strong focus on real-time applications. Written in optimized C/C++, the library can take advantage of multi-core processing. Enabled with OpenCL, it can take advantage of the hardware acceleration of the underlying heterogeneous compute platform.
Caffe: a fast open framework for deep learning. Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license.
TensorFlow Tutorial and Examples for Beginners with Latest APIs
A complete daily plan for studying to become a machine learning engineer.
Deep Learning Book Chinese Translation
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
Tensors and Dynamic neural networks in Python with strong GPU acceleration. PyTorch is a Python package that provides two high-level features: Tensor computation (like NumPy) with strong GPU acceleration Deep neural networks built on a tape-based autograd system. You can reuse your favorite Python packages such as NumPy, SciPy and Cython to extend PyTorch when needed.
The most cited deep learning papers
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet. Detectron is Facebook AI Research's software system that implements state-of-the-art object detection algorithms, including Mask R-CNN. It is written in Python and powered by the Caffe2 deep learning framework. The goal of Detectron is to provide a high-quality, high-performance codebase for object detection research. It is designed to be flexible in order to support rapid implementation and evaluation of novel research.
Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
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.
Oxford Deep NLP 2017 course
Machine LearningDeep LearningPostgreSQLDistributed SystemNode.JsGolang
A neural network that transforms a screenshot into a static website
Face recognition with deep neural networks.
Essential Cheat Sheets for deep learning and machine learning researchers
Industrial-strength Natural Language Processing (NLP) with Python and Cython
pix2code: Generating Code from a Graphical User Interface Screenshot
Deeplearning4j, ND4J, DataVec and more - deep learning & linear algebra for Java/Scala with GPUs + Spark - From Skymind
A curated list of awesome Deep Learning tutorials, projects and communities.
Machine Learning From Scratch. Bare bones Python implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from data mining to deep learning.
Dive into Machine Learning with Python Jupyter notebook and scikit-learn!
Style transfer, deep learning, feature transform
Convolutional Neural Networks
Deep learning library featuring a higher-level API for TensorFlow.
Super Resolution for images using deep learning.
An awesome Data Science repository to learn and apply for real world problems.
Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch
Caffe2 is a lightweight, modular, and scalable deep learning framework.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
machine learning and deep learning tutorials, articles and other resources
OpenPose: Real-time multi-person keypoint detection library for body, face, and hands estimation
TensorFlow tutorials and best practices.
PArallel Distributed Deep LEarning
A TensorFlow implementation of Baidu's DeepSpeech architecture
Code samples for my book "Neural Networks and Deep Learning"
A curated list of deep learning resources for computer vision
Turi Create simplifies the development of custom machine learning models.
Minimal and clean examples of machine learning algorithms implementations
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
TensorFlow CNN for fast style transfer
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
PyTorch Tutorial for Deep Learning Researchers
A curated list of resources dedicated to Natural Language Processing (NLP)
The Swift machine learning library.
The fast.ai deep learning library, lessons, and tutorials
A toolkit for making real world machine learning and data analysis applications in C++
Hide screen when boss is approaching.
Recurrent Neural Network - A curated list of resources dedicated to RNN
Image-to-image translation with conditional adversarial nets
Image super-resolution through deep learning
Face recognition using Tensorflow
NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.
TensorFlow Tutorials with YouTube Videos
Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen /faster_rcnn for the official MATLAB version
Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).
A list of popular github projects related to deep learning
Image-to-image translation in PyTorch (e.g., horse2zebra, edges2cats, and more)
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
header only, dependency-free deep learning framework in C++14
Deep Scalable Sparse Tensor Network Engine (DSSTNE) is an Amazon developed library for building Deep Learning (DL) machine learning (ML) models
Run Keras models in the browser, with GPU support using WebGL
ncnn is a high-performance neural network inference framework optimized for the mobile platform
A series of Docker images (and their generator) that allows you to quickly set up your deep learning research environment.
This research aims at simply deploying deeplearning on mobile and embedded devices, with low complexity and high speed. old name mobile deep learning.
Efficient Deep Learning Development
A technical report on convolution arithmetic in the context of deep learning
A flexible framework of neural networks for deep learning
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers
Simple and ready-to-use tutorials for TensorFlow
Deep Residual Learning for Image Recognition
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Keras code and weights files for popular deep learning models.
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
Open Neural Network Exchange
LabelImg is a graphical image annotation tool and label object bounding boxes in images
Intel Nervana reference deep learning framework committed to best performance on all hardware
A MNIST-like fashion product database. Benchmark
Summaries and notes on Deep Learning research papers
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.
A high-performance distributed execution engine
Convolutional Neural Network for Text Classification in Tensorflow
Deep Learning Tutorial notes and code. See the wiki for more info.
Code examples for new APIs of iOS 10.
Code for Tensorflow Machine Learning Cookbook
Deep Learning GPU Training System
Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning
Unity Machine Learning Agents Toolkit
Open Source Fast Scalable Machine Learning Platform For Smarter Applications (Deep Learning, Gradient Boosting, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles, Automatic Machine Learning (AutoML), ...)
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices
MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
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.
Code for "Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression"
Image augmentation for machine learning experiments.
An all-in-one Docker image for deep learning. Contains all the popular DL frameworks (TensorFlow, Theano, Torch, Caffe, etc.)
An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch.
Interactive Image Generation via Generative Adversarial Networks
Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV.
Distributed training framework for TensorFlow, Keras, and PyTorch.
Papers about deep learning ordered by task, date. Current state-of-the-art papers are labelled.
Deep Reinforcement Learning for Keras.
Basic Machine Learning and Deep Learning
Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).
Code repo for realtime multi-person pose estimation in CVPR'17 (Oral)
MXNet / Gluon
BigDL: Distributed Deep Learning Library for Apache Spark
A recurrent neural network for generating little stories about images
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
Deep Learning (Python, C, C++, Java, Scala, Go)
TensorFlow Basic Tutorial Labs
Simple and comprehensive tutorials in TensorFlow
An open-source NLP research library, built on PyTorch.
A Neural Net Training Interface on TensorFlow
Repo for the Deep Learning Nanodegree Foundations program.
mlpack: a scalable C++ machine learning library --
Deep Learning Porn Video Classifier/Editor with Caffe
A clear, concise, simple yet powerful and efficient API for deep learning.
Directory of tutorials and open-source code repositories for working with Keras, the Python deep learning library
Deep learning driven jazz generation using Keras & Theano!
all kinds of text classificaiton models and more with deep learning
A best practice for tensorflow project template architecture.
TensorFlow & Deep Learning Tutorial
Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"
End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow
Evaluation of Deep Learning Frameworks
Deep Learning Specialization by Andrew Ng on Coursera.
A course in reinforcement learning in the wild
Introduction to Deep Neural Networks with Keras and Tensorflow
Programming exercises for the Stanford Unsupervised Feature Learning and Deep Learning Tutorial
Multi-layer Recurrent Neural Networks (LSTM, RNN) for character-level language models in Python using Tensorflow
Instructions for setting up the software on your deep learning machine
Synthesizing and manipulating 2048x1024 images with conditional GANs
A distributed visual search and visual data analytics platform.
Image augmentation library in Python for machine learning.
Gorgonia is a library that helps facilitate machine learning in Go.
Efficient, reusable RNNs and LSTMs for torch
Practical tutorials and labs for TensorFlow used by Nvidia, FFN, CNN, RNN, Kaggle, AE
Minimal and Clean Reinforcement Learning Examples
Create Anime Characters with MakeGirlsMoe
My tensorflow implementation of "A neural conversational model", a Deep learning based chatbot
Single Shot MultiBox Detector in TensorFlow
An interactive book on deep learning. Much easy, so MXNet. Wow.
Keras implementations of Generative Adversarial Networks.
Deep Learning Chinese Word Segment
Deep Learning for NLP resources
An open source library for deep learning end-to-end dialog systems and chatbots.
Tensorflow tutorial from basic to hard
TensorFlow (Python API) implementation of Neural Style
A simple interface for editing natural photos with generative neural networks.
Open Source Neural Machine Translation in Torch
Source-to-Source Debuggable Derivatives in Pure Python
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
An End-To-End, Lightweight and Flexible Platform for Game Research
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
2D and 3D Face alignment library build using pytorch
Text to image synthesis using thought vectors
A collection of machine learning examples and tutorials.
Deep learning with dynamic computation graphs in TensorFlow
Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning
Simplified implementations of deep learning related works
Automatic colorization using deep neural networks. "Colorful Image Colorization." In ECCV, 2016.
A platform to visualize the deep learning process.
Deep Learning toolkit for Computer Vision
Speech recognition using the tensorflow deep learning framework, sequence-to-sequence neural networks
A recurrent neural network designed to generate classical music.
Deep Learning API and Server in C++11 with Python bindings and support for Caffe, Tensorflow, XGBoost and TSNE
Deep learning software for colorizing black and white images with a few clicks.