GitHub as the world’s leading software development platform is one of the best places to learn data science. There are several reasons why programmers use Github. The main reasons are:
- Git is a distributed version control system in the cloud that lets multiple people write, change and modify code simultaneously. All the changes & the version history are stored in the cloud thus making it easy for programmers that are working on the project to access the files seamlessly.
- This was a revolutionary concept when introduced and the community of developers that Github has managed to bring under its fold has only grown over the years. The absolute number of people using Github outmatches its competitors like Bitbucket and SourceForge by a margin.
- Github is an open-source repository and has no barriers to entry. You can use pretty much any programming language under the sun and contribute to the top repositories on Github.
- Github is amazingly fast since it is decentralized.
- You can work with a wide array of tools and can merge multiple Github repositories as you wish. It also gives developers a lot of freedom to experiment.
Now, let us take a glance on how to use Github for each popular Github repository in this article and how it can help you in the path to becoming a talented data scientist.
CV or Computer Vision has been a rapidly growing field in data science when it comes to popularity and the use cases. In this library, you could find:
- An inclusive list of functions related to facial recognition.
- Tricks to improve performance when it comes to training models and enhancement of the existing models.
- A lot of backbone support (including LightCNN, MobileNet, etc..)
- Help and support in data pre-processing
This is one of the best GitHub private repository for people who are interested in practical applications related to facial recognition and computer vision.
One of the most popular NLP Github repository, Google’s AI team has been amongst the most prolific contributor to this repository.
This GitHub data science repository provides a lot of support to Tensorflow and PyTorch. And if you are someone who is struggling with long-range dependencies, then transformer-XL goes a long way in bridging the gap and delivers top-notch performance in NLP.
The repository was created by Microsoft to help .NET developers in learning machine learning concepts. The repository is an open-source project that lets anyone create models in .NET.
The best part about ML.Net when comparing it with other Github repositories of a similar category is that you can integrate the already present ML models into your application, without having a deep understanding of how the model might work. This repository is used in a medley of Microsoft offerings like Bing and Windows.
This repository by the Facebook AI research team helps people in executing & implementing the latest facial and other types of detection frameworks. Written in Python, it is a fairly comprehensive repository with nearly 100 existing models.
If you are someone who is passionate about data visualization, then this Github repository would be a great resource for you. We all understand that a deep learning model involves multiple mini-tasks that work seamlessly only when combined. VisualIDL does a great job in supporting multiple components including scalar, histogram, image, audio, and graph.
6. NLP Progress
Created by Sebastian Ruder, a research scientist at DeepMind, NLP Progress is one of the best repositories in Github when it comes to Natural Language Programming. The repository contains a lot of datasets and up to date models that you can use in your NLP project.
The quality of the repository is quite high and contains the knowledge of the latest trends and techniques in NLP. If you are passionate about NLP, this is one library that you should not miss out on.
If you are someone who is not very proficient in programming and wish to train deep learning models, then you have come to the right place. Based on Google’s deep learning platform, TensorFlow, you can build ensemble models and train neural networks via this repository.
There is also a lot of API documentation and other info for you to understand the concepts better.
If you are someone who has mastered the basic data science concepts of github repository and are looking to get your hands dirty on advanced topics like reinforcement learning, this is a Github repository that can provide you solace.
There are many examples of reinforcement learning in this Github repository which can be used in your practical projects.
I hope you enjoyed reading this Github tutorial for beginners found it useful.
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