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Understanding Linear Regression [Part 10] | Machine Learning for Beginners
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Machine Learning for Beginners - Understanding Linear Regression [Part 10] | Machine Learning for Beginners

Master Machine Learning: From Basics to Regression Mastery with Microsoft Developer!

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13 learners

What you'll learn

Understand the fundamentals and history of machine learning.
Learn how to set up the tools and environment necessary for building machine learning models.
Apply linear and logistic regression techniques to real-world datasets.
Analyze and visualize data effectively using tools like Matplotlib.

This course includes

  • 1 hours of video
  • Certificate of completion
  • Access on mobile and TV

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Full Transcript

📈 In this video, Bea Stollnitz, a Principal Cloud Advocate at Microsoft, helps you understand the concept of linear regression, a fundamental machine learning algorithm. This video is part of our Machine Learning for Beginners series, where we cover various machine learning topics and their implementation using Python code in Jupyter notebooks. In this video, you'll learn: ✅ What linear regression is and how it works ✅ How to interpret the parameters of a linear regression model ✅ The concept of least-squares regression ✅ How linear regression can be extended to multiple features We'll start with a one-dimensional scenario, where we have a single feature x, and explain how linear regression finds the best line that approximates the general shape of a cloud of data points. We'll discuss the concepts of error minimization and the least-squares method. Then, we'll briefly touch on how linear regression can be extended to multiple features. By the end of this video, you'll have a solid understanding of the core concepts behind linear regression, preparing you for the next video in our series, where we'll discuss correlation and its importance when training linear regression models. Make sure to subscribe and hit the notification bell 🔔 so you won't miss our upcoming videos, where we'll dive deeper into various machine learning topics and guide you through their implementation using Python code in Jupyter notebooks. See you there! 0:00 - Intro 0:13 - What is linear regression? 1:10 - Least squares regression 1:27 - Multidimensional linear regression for multiple features. 1:52 - The mathematical function for 1 dimensional linear regression 📙 Follow along: The Jupyter Notebook to follow along with this lesson is available here: https://github.com/microsoft/ML-For-Beginners/tree/main/2-Regression/3-Linear #LinearRegression #MachineLearning #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

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