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Trending Big Data GitHub Repositories

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GitHub is much more than a software versioning tool, which it was originally meant to be. Now people from different backgrounds and not just software engineers are using it to share their tools / libraries they developed on their own, or even share resources that might be helpful for the community.

Here are some popular new repositories that can be interesting for Data Scientist. 

 . . . 

Awesome Data Science
This GitHub repository is an ultimate resource guide to data science. It is built upon multiple contributions over the years with links to resources ranging from getting-started guides, infographics to people to follow on social networking sites like twitter, facebook, Instagram etc. There are plenty of resources waiting to be viewed, irrespective of whether you are a beginner or a veteran.

https://github.com/bulutyazilim/awesome-datascience
Deep Learning Cheat Sheets 
This repository consists of the commonly used tools and techniques compiled in the form of cheatsheets. The cheatsheets range from very simple tools like pandas to techniques like Deep Learning. After giving a star or forking the repository, you won’t need to google the most commonly used tips and tricks.

https://github.com/kailashahirwar/cheatsheets-ai

Oxford Deep NLP 2017
Stanford NLP has always been a golden course for people wanting to venture out into the field of Natural Language Processing. But with the advent of Deep Learning, NLP has seen tremendous progress, all thanks to the capabilities of Deep Learning Architectures such as RNN and LSTMs.This repository based on Oxford NLP Lectures take the education of NLP to next level. A practical course, these lectures covers the techniques and terminologies to advance material such as using RNNs for Language Modeling, Speech Recognition, Text to Speech etc. This repository is a one stop shop for all the materials of the Oxford Lectures providing Lecture materials to Practical assignments.

https://github.com/oxford-cs-deepnlp-2017/lectures

NIPS 2017
This repository is a list of resources and slides of all invited talks, tutorials, and workshops in NIPS 2017 conference. For those who do not know what NIPS is, it is an annual conference specifically for Machine learning and Computational Neuroscience.Most of the breakthrough research that has happened in the data science industry in the last couple of years has been a result of the research that has been presented at this conference. If you want to stay ahead of the curve, this is the right resource to follow!

https://github.com/hindupuravinash/nips2017

PyTorch 
As of now, PyTorch is the sole competitor to Tensorflow and it is doing a good job of maintaining its reputation. With the ease of Pythonic style coding, Dynamic Computations, and faster prototyping, PyTorch has garnered enough attention of the Deep Learning Community.
https://github.com/yunjey/pytorch-tutorial
Written by

Amir Arres has been the Editor in Chief of Dataism since November 2015. He directs its strategy and development. He has a background in Data Analysis and a BA in Business Decision Making. Amir is interested in how new thinking from Big Data challenges conventional ways of understanding knowledge and culture. His vision for Dataism is to create a sanctuary online for bold and nuanced ideas.