Machine Learning for Beginners - Introduction to Regression models for Machine Learning [Part 5] | 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. Don't forget to subscribe and hit the notification bell 🔔 so you won't miss the next video in this series, where we'll dive deeper into linear regression and guide you through its implementation. See you there! #MachineLearning #RegressionModels #Python #ML 📚 Learn more: This course is based on the free, open source, 26 lesson ML For Beginners curriculum from Microsoft, which can be found at https://aka.ms/ml-beginners. 📇 Connect with Bea: Blog: https://bea.stollnitz.com/blog/ LinkedIn: https://www.linkedin.com/in/beatrizstollnitz/ Twitter: https://twitter.com/beastollnitz 0:00 - Intro 0:09 - What are regression models? 0:55 - The 3 major types of regression 1:08 - Linear regression 1:47 - Polynomial regression 2:22 - Logistic regression