In my last series of posts on Transformers, I talked about how a transformer works and how to implement one yourself for a translation task.

Finally, my program is running! Should I go and get a coffee?

Algorithms are an integral part of data science. While most of us data scientists don’t take a proper algorithms course while studying, they are important all the same.

In my last post on BERT , I talked in quite a detail about BERT transformers and how they work on a basic level.

In my last post , I talked about Object-Oriented Programming(OOP). And I specifically talked about a single magic method __init__ which is also called as a constructor method in the OOP terminology.

Python in many ways has made our life easier when it comes to programming.

Object-Oriented Programming or OOP can be a tough concept to understand for beginners.

Transformers have become the defacto standard for NLP tasks nowadays. They started being used in NLP but they are now being used in Computer Vision and sometimes to generate music as well.

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?