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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
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
Ridge and Lasso Regression
Posted inMachine Learning

Ridge and Lasso Regression

Introduction In this post we will try to understand about regularization and hyperparameter-tuning using Ridge and Lasso Regression. Before that we need to understand few concepts of Linear Regression. I…
Posted by tkhan.kiit@gmail.com July 4, 2020
Math behind Simple Linear Regression
Posted inMachine Learning

Math behind Simple Linear Regression

Simple Linear Regression In this post we will try to understand the Math behind Simple Linear Regression. But before getting into the details let’s understand what Simple Linear Regression means. Simple…
Posted by tkhan.kiit@gmail.com June 28, 2020
K-Nearest Neighbour
Posted inMachine Learning

Mathematical assumptions while solving problems using Regression

Introduction Understanding the math behind any algorithm is very important. Often we dive straight into solving a problem using some machine learning algorithm and applying all sorts of techniques without…
Posted by tkhan.kiit@gmail.com May 31, 2020
Linear Regression
Posted inMachine Learning

Linear Regression

The figure that you are seeing above details the various steps in data preprocessing as well as the Linear regression. We have covered the data preprocessing steps in detail here.…
Posted by tkhan.kiit@gmail.com May 14, 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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