Ultimate ML Bootcamp #2: Linear Regression

Ultimate ML Bootcamp #2: Linear Regression, available at Free, with 13 lectures, and has 50 subscribers.

You will learn about Understand the principles and applications of linear regression in predictive modeling and data analysis. Calculate and interpret the weights (coefficients) in a linear regression model to understand relationships between variables. Evaluate the performance of linear regression models using key metrics such as R-squared and Mean Squared Error (MSE). Implement and optimize linear regression models using techniques like gradient descent for both simple and multiple regression scenarios. This course is ideal for individuals who are Ideal for beginners in machine learning and data science who want to gain a strong understanding of linear regression or Suitable for professionals looking to enhance their predictive modeling skills It is particularly useful for Ideal for beginners in machine learning and data science who want to gain a strong understanding of linear regression or Suitable for professionals looking to enhance their predictive modeling skills.

Enroll now: Ultimate ML Bootcamp #2: Linear Regression

Summary

Title: Ultimate ML Bootcamp #2: Linear Regression

Price: Free

Number of Lectures: 13

Number of Published Lectures: 13

Number of Curriculum Items: 13

Number of Published Curriculum Objects: 13

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

Understand the principles and applications of linear regression in predictive modeling and data analysis.
Calculate and interpret the weights (coefficients) in a linear regression model to understand relationships between variables.
Evaluate the performance of linear regression models using key metrics such as R-squared and Mean Squared Error (MSE).
Implement and optimize linear regression models using techniques like gradient descent for both simple and multiple regression scenarios.

Who Should Attend

Ideal for beginners in machine learning and data science who want to gain a strong understanding of linear regression
Suitable for professionals looking to enhance their predictive modeling skills

Target Audiences

Ideal for beginners in machine learning and data science who want to gain a strong understanding of linear regression
Suitable for professionals looking to enhance their predictive modeling skills

Welcome to the second chapter of Miuul’s Ultimate ML Bootcamp—a comprehensive series designed to take you from beginner to expert in the world of machine learning and artificial intelligence. This course, Ultimate ML Bootcamp #2: Linear Regression, builds on the foundation you’ve established in the first chapter and dives deep into one of the most fundamental techniques in machine learning—linear regression.

In this chapter, you’ll explore the principles and applications of linear regression, a critical tool for predictive modeling and data analysis. We’ll start by defining what linear regression is and why it’s so essential in both machine learning and statistical modeling. You’ll then learn how to calculate the weights (coefficients) that define your regression model, and how to evaluate its performance using key metrics.

As you progress, you’ll delve into more advanced topics such as parameter estimation, gradient descent optimization, and the differences between simple and multiple linear regression models. We’ll cover both theoretical concepts and practical applications, ensuring that you can confidently apply linear regression to real-world datasets.

This chapter is designed with a hands-on approach, featuring practical exercises and real-life examples to reinforce your learning. You’ll gain experience not only in building and evaluating models but also in understanding the mathematical foundations that underlie these techniques. Whether you’re looking to enhance your predictive modeling skills, prepare for more complex machine learning tasks, or simply deepen your understanding of linear regression, this chapter will provide the knowledge and tools you need.

By the end of this chapter, you’ll have a solid grasp of linear regression, equipped with the skills to build, evaluate, and optimize both simple and multiple linear regression models. You’ll also be well-prepared to tackle more advanced techniques in the subsequent chapters of Miuul’s Ultimate ML Bootcamp. We’re excited to continue this journey with you, and we’re confident that with dedication and practice, you’ll master the art of linear regression and beyond. Let’s dive in!

Course Curriculum

Chapter 1: Linear Regression

Lecture 1: Course Materials

Lecture 2: What is Linear Regression?

Lecture 3: Calculating the Weights

Lecture 4: Model Evaluation in Linear Regression

Lecture 5: Estimation of Parameters

Lecture 6: Gradient Descent for Linear Regression

Lecture 7: Simple Linear Regression Model

Lecture 8: Prediction in Simple Linear Regression

Lecture 9: Model Evaluation in Simple Linear Regression

Lecture 10: Multiple Linear Regression Model

Lecture 11: Prediction in Multiple Linear Regression

Lecture 12: Model Evaluation in Multiple Linear Regression

Lecture 13: Linear Regression with Gradient Descent

Instructors

Miuul Data Science & Deep Learning
Data Science Team of Miuul.com

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Frequently Asked Questions

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