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Heteroscedasticity
Posted inMachine Learning

Heteroscedasticity in Logistic Regression

In simple terms, homoscedasticity means that the spread (or variance) of the residuals (the differences between observed and predicted values) remains constant across all levels of the predicted values. In…
Posted by tkhan.kiit@gmail.com November 24, 2024
Machine Learning Project
Posted inMachine Learning

End to End Machine Learning Project – Part 2

This Post is a continuation of the part 1 where we discussed about the various steps that should be kept in mind before starting a project in machine learning.  To…
Posted by tkhan.kiit@gmail.com October 6, 2024
supervised learning
Posted inMachine Learning

End to End Machine Learning Project – Part 1

This post is part 1 of approaching a machine learning project. Given a problem statement, we will try to see how this can be solved using machine learning and what…
Posted by tkhan.kiit@gmail.com October 6, 2024
Feature Scaling
Posted inArtificial Intelligence and Machine Learning Exploratory Data Analysis

Feature Scaling

What is Feature Scaling Feature Scaling is a preprocessing step in Machine Learning that involves transforming the features of your dataset onto a similar scale. The primary purpose of Feature…
Posted by tkhan.kiit@gmail.com February 12, 2024
Multiple Linear Regression
Posted inMachine Learning

Multiple Linear Regression

In this post, we will go over all the nitty gritty details around Multiple Linear Regression, but first let's start with understanding what is Multiple Linear Regression. Multiple linear regression…
Posted by tkhan.kiit@gmail.com February 8, 2024
Cost Function
Posted inMachine Learning

Mathematical derivation of Cost Function and Gradient Descent

In Linear Regression, Cost Function and Gradient Descent are considered fundamental concepts that play a very crucial role in training a model. Let's try to understand this in detail and…
Posted by tkhan.kiit@gmail.com January 28, 2024
Pros and Cons of Implementing Linear Regression
Posted inMachine Learning

Pros and Cons of Implementing Linear Regression

Linear regression is a statistical method that can be used to model the relationship between a dependent and one or more independent variables. Now you might be wondering, this is…
Posted by tkhan.kiit@gmail.com January 27, 2024
Machine Learning Algorithm
Posted inMachine Learning

Machine Learning Algorithm

In this post, we will discuss about the various Machine Learning Algorithm. The main objective of this blog is to give you a basic level of understanding on what are…
Posted by tkhan.kiit@gmail.com December 22, 2020
Introduction to Machine Learning
Posted inMachine Learning

Introduction to Machine Learning

This blog will be more theoretical introduction towards what is Machine Learning and its different paradigms. So, let’s take a typical definition of Machine Learning and then break it down…
Posted by tkhan.kiit@gmail.com May 2, 2020
Simple Linear Regression
Posted inMachine Learning

Simple Linear Regression

Introduction What is Simple Linear Regression Simple Linear Regression basically defines the relation between a one feature and the outcome variable. This can be specified using the formula y =…
Posted by tkhan.kiit@gmail.com April 13, 2020
Recent Blogs
  • Logistic Regression : Practical Example
  • Cooks Distance – Absence of Outliers or Influential Points
  • Heteroscedasticity in Logistic Regression
  • End to End Machine Learning Project – Part 2
  • End to End Machine Learning Project – Part 1
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Recent Posts
  • Logistic Regression : Practical Example
  • Cooks Distance – Absence of Outliers or Influential Points
  • Heteroscedasticity in Logistic Regression
  • End to End Machine Learning Project – Part 2
  • End to End Machine Learning Project – Part 1
  • Feature Scaling
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