I love working with shell commands. They are fast and provide a ton of flexibility to do ad-hoc things.

Before I even begin this article, let me just say that I love iPython Notebooks, and Atom is not an alternative to Jupyter in any way.

Just recently, I had written a simple tutorial on FastAPI, which was about simplifying and understanding how APIs work, and creating a simple API using the framework.

Have you ever been in a situation where you want to provide your model predictions to a frontend developer without them having access to model related code?

Python provides us with many styles of coding. And with time, Python has regularly come up with new coding standards and tools that adhere even more to the coding standards in the Zen of Python.

Have you ever been frustrated by doing data exploration and manipulation with Pandas?

A Machine Learning project is never really complete if we don’t have a good way to showcase it.

A Machine Learning project is never really complete if we don’t have a good way to showcase it.

Data manipulation is a breeze with pandas, and it has become such a standard for it that a lot of parallelization libraries like Rapids and Dask are being created in line with Pandas syntax.

We as data scientists have got laptops with quad-core, octa-core, turbo-boost.