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Platforms to practice Machine Learning skills

Google Colab:  Google Colaboratory or “Colab” for short, is a product from Google Research. Google Colab allows anybody to write and execute arbitrary python code through the browser, and is especially well suited to machine learning, data analysis and education. Google Colaboratory is a platform built on top of the Jupyter Notebook environment, It provides GPU which is free of cost and supports Python 2 and 3 versions. With the help of Colab, one can not only improve machine learning coding skills but also learn to develop deep learning applications. You can also learn to work with popular deep learning libraries such as Keras, TensorFlow, OpenCV and others. With Colaboratory you can write and execute code, save and share your analyses, and access powerful computing resources, all for free from your browser.

Kaggle: Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. With over 19,000 public datasets and 200,000 public notebooks, This cloud computational environment supports Python 3 and R and enables reproducible and collaborative analysis where one can explore and run machine learning codes seamlessly.

Zindi: Zindi gives African data scientists a place to learn new skills, grow through competitions, community and access work opportunities. Zindi allows you to test your skill on real world data, build models that solve the world’s toughest challenges and also earn cash while doing it. It also allows you to collaborate and connect with data scientists from Africa and beyond. 

OpenML: OpenML is an open science platform for machine learning, It is a cross-platform programming environment for sharing and organising data, machine learning algorithms, and experiments. It is an online Machine Learning (ML) experiments database accessible to everyone for free. OpenML is one of the perfect environments to explore and reuse the best solutions for specific analysis problems as well as interact with the scientific community.

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