Today we’re announcing that Facebook AI has built and open-sourced BlenderBot, the largest-ever open-domain chatbot. It outperforms others in terms of...

We are not just going to solve another reinforcement learning environment but going to create one from scratch.

Understand the difference between between commonly used boosting algorithms. Learn how GBM, XGboost, LightBoost and CatBoost work!

Hint: 98% Accuracy on MNIST with only 5 lines of code!

A step by step guide for implementing one of the most trending machine learning algorithm using numpy

You might have come across Judea Pearl's new book, and a related interview which was widely shared in my social bubble. In the interview, Pearl dismisses most of what we do in ML as curve fitting. While I believe that's an overstatement (conveniently ignores RL for example), it's a nice...

fastai is a modern, open source, deep learning library which is organized around two main design goals: to be approachable and rapidly productive, while also being deeply hackable and configurable

that using a layered API in deep learning has very significant benefits for researchers, practitioners, and students. Researchers can see links across different areas more easily, rapidly combine and restructure ideas, and run experiments on top of strong baselines. Practitioners can quickly build prototypes, and then build on and optimize those prototypes by leveraging fastai’s PyTorch foundations, without rewriting code. Students can experiment with models and try out variations, without being overwhelmed by boilerplate code when first learning ideas.