Arthur Samuel coined the term “Machine Learning” in 1959 and defined it as a “Field of study that gives computers the capability to learn without being explicitly programmed”.

According to recent research of PWC, 72% of business leaders said they believe AI is going to be fundamental in the future and they termed it a “business advantage”.

Natural Language Processing (NLP) is an increasingly important sub-domain of Machine Learning that deals with deriving general understanding through developing various language models from various large corpora of text. In this article, we go over 5 common types of NLP problems and their relevant models.

Getting Started With fast.ai

Find face edges in 20 lines of code from scratch algorithm

A compendium of resources for crafting a curriculum on artificial intelligence, machine learning, and deep learning.

Empowering you to use machine learning to get valuable insights from data.

This list of top machine learning tools is just the start and will continue to be updated.

Explore the Machine Learning Tutorial Series and learn ML from Scratch

In this post, we will discuss the most popular and important ML/DL libraries in the world right now.