In this post, you will learn the concepts of Stochastic Gradient Descent (SGD) using a Python example. Stochastic gradient descent is…
In linear regression, dummy variables are used to represent the categorical variables in the model. There are a few different…
In relation to machine learning, linear regression is defined as a predictive modeling technique that allows us to build a…
In this blog post, we'll be discussing correlation concepts, matrix & heatmap using Seaborn. For those of you who aren't…
There are many clustering machine learning algorithms to choose from when you want to cluster data. But which one should…
Time-series machine learning models are becoming increasingly popular due to the large volume of data that is now available. These…
Alteryx is a self-service data analytics software platform that enables users to easily prep, blend, and analyze data all in…
Hate speech is a big problem on the internet. It can be found on social media, in comment sections, and…
Are you interested in learning the concepts of machine learning with Graphs? Stanford University is offering a free online course…
Business analytics is a business function that has been around for years, but it's only recently gained traction as one…
This page lists down 40 regression (linear/univariate, multiple/multilinear/multivariate) interview questions (in form of objective questions) which may prove to be…
In this post, you will learn about some of the common success metrics that can be used for measuring the…
Warehouses are a vital part of the supply chain. Not only do they store products, but warehouses also play a…
This article describes Type I and Type II errors made due to incorrect evaluation of the outcome of hypothesis testing,…
Cybersecurity professionals are increasingly finding cybersecurity machine learning use cases in their work. The reason for this is that cybersecurity…
In K-means clustering, elbow method and silhouette analysis or score techniques are used to find the number of clusters in…