How Gradient Descent Converges? (Explained with Linear Regression concept)

Welcome to our latest video on Gradient Descent and Linear Regression! 🚀

In this video, we delve deep into the heart of machine learning, exploring how the Gradient Descent algorithm converges to find the optimal solution. We'll be using the concept of Linear Regression as a real-world example to illustrate this fascinating process.

Here's what you can expect from this video:

1. Introduction to Gradient Descent: We kick things off with a comprehensive introduction to Gradient Descent, explaining what it is and why it's so crucial in machine learning.

2. Linear Regression Concept: Next, we'll introduce the concept of Linear Regression and how it's used in predictive modelling.

3. Gradient Descent in Action: We'll then demonstrate how Gradient Descent is used in Linear Regression to minimize the cost function and find the best-fit line.

4. Convergence of Gradient Descent: Finally, we'll explain how Gradient Descent converges, using intuitive visuals and easy-to-understand language.

Whether you're a machine learning enthusiast, a data science student, or a seasoned professional looking to brush up on your skills, this video is for you! So, sit back, grab a cup of coffee, and let's dive into the world of Gradient Descent and Linear Regression!

Don't forget to like, share, and subscribe to our channel for more educational content on machine learning and data science. Leave your questions and comments below - we love hearing from you!

LinkedIn: Anuraaga Nath
Github: Anuraaga Nath