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…
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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…
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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…
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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…
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Bias and Variance in Machine Learning
Introduction to Bias and Variance Bias and Variance plays a very important role while building a model. To frame it in simple terms Bias is interpreted as the model error…
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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…
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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…
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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.…
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Regression Metrics
Introduction This post will be more theoretical and would explain in detail about the different Regression Metrics involved in Regression Models and what are their advantages and disadvantages. While we…
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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 =…