BERT Explained: A Complete Guide with Theory and Tutorial

Unless you have been out of touch with the Deep Learning world, chances are that you have heard about BERT —  it has been the talk of the town for the last one year. At the end of 2018 researchers at Google AI Language open-sourced a new technique for Natural Language Processing (NLP) called BERT...

Time Series Forecasting, the easy way! Let’s analyze Microsoft’s stocks

Introduction Time series forecasting and understanding time based patterns have many important applications. However, it is a territory often left unexplored, especially by ML practitioners, because of its relative complexity. To help people with domain knowledge, but without much expertise in creating statistical forecasting model, Facebook decided to come to rescue. And we will see...

Click-Through Rate (CTR) Prediction using Decision Trees

1. Introduction In this tutorial, we will try to predict click-through rate of ads with the Decision Tree algorithm we learnt in the last post. Before continuing, I would recommend you to first read that post for a theoretical understanding of Decision Trees. What does Click-Through Rate Prediction mean? Let's assume that you are designing...

A dataset and a ML problem, what should you do? An end-to-end example with housing dataset from Kaggle

In this post, we will deconstruct the basics of working with a dataset to solve ML problems. This first part of this post gives a quick overview of the general workflow needed to work with ML problems. The second part comprises of a practical end-to-end example in Python. Part 1 The process of working with...