Episode

Introduction to Regression models for Machine Learning (Part 5 of 17) | Machine Learning for Beginners

with Bea Stollnitz

Machine Learning for Beginners

Welcome to the next episode of our Machine Learning for Beginners course, presented by Bea Stollnitz, a Principal Cloud Advocate at Microsoft! In this video, we'll introduce regression models, which are essential tools in machine learning for investigating the relationship between variables.

In this video, you'll learn about:

  • The concept of regression and how it can be used to predict values
  • The differences between linear, polynomial, and logistic regression
  • Real-world examples of how regression models can be applied

We'll be exploring these regression types in more depth in the upcoming videos, where you'll also learn how to implement them using Python code in Jupyter notebooks.

Stay tuned for the next video in this series, where we'll dive deeper into linear regression and guide you through its implementation. See you there!

Chapters

  • 00:00 - Introduction
  • 00:09 - What are regression models?
  • 00:55 - The 3 major types of regression
  • 01:08 - Linear regression
  • 01:47 - Polynomial regression
  • 02:22 - Logistic regression
  • This course is based on the free, open-source, 26-lesson ML For Beginners curriculum from Microsoft.

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