10 useful Github repositories every Data Scientist should bookmark

Data science has become a vital part of modern business decision-making, with organizations of all sizes relying on it to drive growth and success.?With the increasing popularity of the field, more and more individuals are interested in learning about data science.

Gaining hands-on experience is crucial for learning any field, and data science is no exception.

One of the best places to start is GitHub, which offers a wealth of resources for learning and growing in the field.

This is why, I collected 10 different Github repositories that can be useful for any Data Scientist?— either beginners or seniors — who wants to keep learning and improving their skills.

Let’s discover them all together ????

#1. Data Science Roadmap

If you’re looking to become a data scientist, this repository is here to help. It’s based on a roadmap created by Swami Chandrasekaran, and it covers everything you need to know to crush into Data Science and become a succesful data scientist.

From the fundamentals to statistics and programming, and then on to machine learning, data visualization, and data munging —?this GitHub will allow you to crush into Data Science and learn fast!

???Additionally, you’ll find a section dedicated to tools that data scientists commonly use in their work.

#2. Free-programming-books

Books are still an important source of knowledge for any field — and Data Science is no exception.?This GitHub repository contains a huge list of freely available books to learn anything related to programming — be it Python, Machine Learning, or any other!

#3. Awesome repository

The Awesome Github repository provides an organized list of machine learning libraries, frameworks and tools in almost all the languages available.

With libraries like sci-kit-image, CLTK, sci-kit-learn, pandas, and neural_talk,?it’s a one-stop-shop for all your Data Science needs!

#4. A curated list of project-based tutorials

This GitHub repository provides a collection of tutorials for creating projects of any kind.?While it covers a diverse range of subjects useful for any developer out there, it also includes many projects that are especially useful for data scientists.

Learn to build your own app, covering various primary languages, these tutorials guide you from scratch!

#5. Open API

This Github comes in really handy when looking for some reliable data source of any kind. It contains a collective list of free APIs for use in software and web development.?One of my favorites for sure!

#6. The Algorithms

This repository offers a collection of Python algorithms for various domains?such as Machine learning, Neural Networks, Digital Image Processing, and Computer Vision.

It includes codes for regression, classification, backpropagation, Convolutional Neural Networks, edge detection, and pooling, useful for various applications like predictive analysis, image classification, and autonomous cars.

#7. Data Science Python Notebooks

This repository offers python notebooks?on machine learning, data engineering, and data augmentation using popular libraries such as TensorFlow, sci-kit-learn, pandas, and matplotlib.

It includes examples of popular machine learning algorithms, data cleaning, and visualization techniques.

#8. Home-made machine learning

This repo offers?a comprehensive collection of machine learning algorithms, explained with code and mathematics, using Python and Jupyter notebooks.

It covers supervised and unsupervised learning, as well as neural networks, making it a valuable resource for understanding and strengthening the fundamentals of machine learning.

#9. Awesome Data Science

This GitHub repository is essential for those who want to learn the basics of Data Science and Machine Learning, including tutorials and free courses.?It also includes popular libraries, journals, and podcasts for staying up-to-date on the latest developments.

#10. 500 AI-ML Projects

This repository offers a comprehensive list of over 500 projects on machine learning, NLP, and AI, complete with code, to give you hands-on experience in the field.

It’s perfect for students or enthusiasts looking to gain practical knowledge and create projects for their resumes — and get some extra inspiration for your next personal project! :D

Hope you find these resources useful! :)