February 13, 2021

Python testing tutorial using pytest

Testing your code brings a wide variety of benefits. It increases your confidence that the code behaves as you expect and […]
February 8, 2021

Maximum Likelihood Estimation (MLE) and Maximum A Posteriori (MAP) Simply explained

Maximum Likelihood Estimation (MLE) and Maximum A Posteriori (MAP) estimation are method of estimating parameters of statistical models. Despite a […]
February 4, 2021

Implicit Recommender Systems with Alternating Least Squares

http://activisiongamescience.github.io/2016/01/11/Implicit-Recommender-Systems-Biased-Matrix-Factorization/ In today’s post, we will explain a certain algorithm for matrix factorization models for recommender systems which goes by […]
December 18, 2020

How to determine epsilon and MinPts parameters of DBSCAN clustering

Every data mining task has the problem of parameters. Every parameter influences the algorithm in specific ways. For DBSCAN, the […]
November 24, 2020

A review on Deep learning based recommendation systems

Source: https://jameskle.com/writes/rec-sys-part-2 INTRODUCTION The number of research publications on deep learning-based recommendation systems has increased exponentially in the past recent […]
November 20, 2020

Four steps to setup Pytorch for my laptop GPU NVIDIA GTX 960m (Asus VivoBook n552vw) in Ubuntu 16.4

In this post, I’m gonna describe the steps I used to make Pytorch use GPU on my laptop (It takes […]
November 9, 2020

Restricted Boltzmann Machines (RBMs) Simply Explained

Contents Definition & Structure Reconstructions Probability Distributions Code Sample: Stacked RBMS Parameters & k Continuous RBMs Next Steps Other Resources […]
November 5, 2020

Collaborative Filtering based Recommendation methods Explained

https://realpython.com/build-recommendation-engine-collaborative-filtering Collaborative Filtering is the most common technique used when it comes to building intelligent recommender systems that can learn […]