3 Types of Gradient Decent Types : Batch, Stochastic & Mini-Batch _ Day 8

Understanding Gradient Descent: Batch, Stochastic, and Mini-Batch Understanding Gradient Descent: Batch, Stochastic, and Mini-Batch Learn the key differences between Batch Gradient Descent, Stochastic Gradient Descent, and Mini-Batch Gradient Descent, and how to apply them in your machine learning models. Batch Gradient Descent Batch Gradient Descent uses the entire dataset to calculate the gradient of the cost function, leading to stable, consistent steps toward an optimal solution. It is computationally expensive, making it suitable for smaller datasets where high precision is crucial. Formula: \[\theta := \theta – \eta \cdot \frac{1}{m} \sum_{i=1}^{m} \nabla_{\theta} J(\theta; x^{(i)}, y^{(i)})\] \(\theta\) = parameters \(\eta\) = learning...

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Can we make prediction without need of going through iteration ? yes with the Normal Equation _ Day 6

Understanding Linear Regression: The Normal Equation and Matrix Multiplications Explained Understanding Linear Regression: The Normal Equation and Matrix Multiplications Explained Linear regression is a fundamental concept in machine learning and statistics, used to predict a target variable based on one or more input features. While gradient descent is a popular method for finding the best-fitting line, the normal equation offers a direct, analytical approach that doesn’t require iterations. This blog post will walk you through the normal equation step-by-step, explaining why and how it works, and why using matrices simplifies the process. Table of Contents Introduction to Linear Regression Gradient...

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