Medium Link Over the last two decades, recommender systems have become State-of-the-Art Algorithms and can be regarded as success factors for companies such as Google, Amazon, and Netflix. The main objective of a recommender system is to produce relevant recommendations to a collection of users for items that might interest them. This article is a part end-to-end machine learning project series where I will build a web application for a Regression-based Movie Recommender system that is a hybrid of content-based and collaborative filtering algorithm from scratch.

Medium Link When I started with Machine Learning, one of the most troublesome thing that didn’t make much sense was the choice of the Loss function for different Machine learning algorithms, justifications for using the specific loss function for different kinds of ML algorithms were most of the time based on intuition rather any formal mathematical proof this blog discuss the Mathematical Justification for using a specific kind of loss function in different types of supervised Machine learning algorithms through Probability