Visual Studio Code offers many great features for Data Scientists and Python developers alike, allowing you to explore and experiment on your data using the flexibility of Jupyter Notebooks combined with the power and productivity of VS Code. Tune in to learn how to supercharge your Jupyter Notebooks with VS Code.

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Jeffrey Mew shows you how you can can natively edit Jupyter notebooks in Visual Studio Code.

Jupyter (formerly IPython) is an open-source project that enables you to easily combine Markdown text and executable Python source code on one canvas called a notebook.

These notebooks contain live code, equations, visualizations and narrative text. Jeffrey shows how easy it is to work with Jupyter notebooks in Visual Studio Code.

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Kirill Gavrylyuk joins Scott Hanselman to show how to run Jupyter Notebook and Apache Spark in Azure Cosmos DB. Now you can use the interactive experience of Jupyter Notebook and analytics powered by Apache Spark with your operational data. Run analytics and ML on your operational data in real time without data movement, and without the need to split into transactional and analytical silos.

[00:02:18] Jupyter Notebook demo

[00:05:41] Jupyter Notebook + Apache Spark demo     

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Google Colaboratory (Colab) is a cloud service that can be used for free of cost. It supports a free GPU and is based on Google’s Jupyter Notebooks environment. If you’re looking for alternatives, then you’re in luck.  While I am partial to Azure Notebooks, especially when paired with a Data Science Virtual Machine, I appreciate this rundown of other alternatives by Analytics India Magazine.

It provides a way for your machine to not carry the load of heavy workout of your ML operations. It is one of the very popular platforms of the kind. But there are some others which form as efficient alternatives of Colab. These are the best alternatives available out there for Google colab.