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... Continue Reading →
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... Continue Reading →
Understanding Decision Trees
Tree based algorithms are among the most common and best supervised Machine Learning algorithms. Decision Trees follow a human-like decision making approach by breaking the decision problem into many smaller decisions. As opposed to black-box models like SVM and Neural Networks, Decision Trees can be represented visually and are easy to interpret. How is decision... Continue Reading →