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Which Top Machine Learning GitHub Repositories To Seek In 2019?

Which Top Machine Learning GitHub Repositories To Seek In 2019?

Due to various popular recent innovations, machine learning is getting huge importance in a very short time among many web development companies. It is popping up more and going to completely transform the web development scenario of today.

Machine learning uses such algorithms that make computers learn without being explicitly programmed. Hence, it is the best method of data analysis that automates the creation of analytical models. This is the reason why Machine Learning plays an important role in web development.

Here, we will be listing GitHub featured open source projects in machine learning which hosts over 100 million repositories overall. The most popular ones are actually decided by the number of stars given to them.

In this blog, we will discuss top 10 open source projects in Machine Learning which every business must look into. 

Here is the list of ML projects/tools:


1)  TRFL

Pronounced as a truffle, this is a library built on TensorFlow and is useful for building blocks to write reinforcement learning agents (RL) on TensorFlow CPU and GPU versions.

2) PocketFlow 

It is an open source framework that is used to compress and accelerate deep learning models. The main objective is to provide an easy-to-use set of tools to improve the efficiency of developers with minimal performance degradation.

3) AdaNet


It is basically a lightweight network based on TensorFlow and is based on the efforts of AutoML that are used to automatically learn high-quality models with the least interference from experts. The objectives of this project are ease of use, flexibility, speed, and guarantee of learning.

4) DeepCreamPy 

DeepCreamPy is a tool based on deep learning that is used to automatically replace censored illustrations in hentai with possible reconstructions. The features it contains are high-quality images of censorship of any size and shape, support of mosaic elevator and user interface (WIP).

5) Graph Nets 

The operation of Graph Nets is that it takes the graph as input and returns the graph as output. It also validates the deep learning architecture to learn and understand the rules, relationships, and entities in a graph. DeepMind, owned by Google and based in London, opened the graphics networking library in October. It can be installed and used in TensorFlow.

6) BERT 

BERT(Bidirectional Encoder Representations from Transformers) is a completely new method of previous training in the representations of language. It is the first unsupervised and deeply bidirectional system for natural language processing (NLP) pre-training and obtains new state-of-the-art results in eleven NLP tasks. This repository contains TensorFlow code and pre-trained models for BERT.

7) Maskrcnn-Benchmark 

Launched under the MIT license, this project mainly uses PyTorch 1.0 and aims to provide the necessary components to create detection and segmentation models without any difficulty.

8) Horizon 

This is an end-to-end open source platform for learning applied reinforcement (applied RL), built in Python that uses PyTorch to model and train, as well as Caffe2 for model service. It is mainly used on Facebook and algorithms such as Soft Actor-Critic (SAC), DDPG, DQN are supported here.

9) DeOldify 

DeOldify by Jason Antic, the name says it all. It is a project based on deep learning that is used to color and restore old black and white images to a colorful one.

10) MAME RL Algorithm Training Toolkit 

This Python library is used in almost all arcade games to train a reinforcement learning algorithm. Based on the Linux operating system with version 3.6+, it allows your algorithm to go through the game while receiving and sending actions to interact with the game.


So far we have seen some top machine learning projects by Github for your web development. In fact, web development with machine learning is going to revolutionize the IT world. However, the various popular Machine Learning frameworks and libraries are written in or primarily supported by Python that includes Keras, Theano, TensorFlow and smaller projects like Microsoft Azure Studio, sci-kit learn, Veles, Chainer, Neon.

So if you are curious to develop your next project with one of these machine learning frameworks, then it is the right time to start with. You can also hire skilled ML web developers from a reliable web development company like ValueCoders.

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