Linear Regression in Python | Data Science with Marco

Data Science with Marco · Beginner ·📐 ML Fundamentals ·6y ago

Key Takeaways

This video covers simple and multiple linear regression in Python, including theoretical aspects such as estimating coefficients, understanding the error function, and hypothesis testing, as well as hands-on examples using Python code and a notebook available on GitHub.

Original Description

Get the notebook: https://github.com/marcopeix/datasciencewithmarco 📚Theory: 0.00 - 3:24 🐍Code: 3:25 - 15:05 In this video, we will cover simple and multiple linear regression. We will cover the theoretical aspects of linear regression such as: - how to estimate coefficients - understanding the error function - hypothesis testing for the coefficients - how to assess the relevance of our linear model We finish this lesson with hands-on examples to apply the theory.
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▶ Linear Regression in Python | Data Science with Marco
Linear Regression in Python | Data Science with Marco
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Data Science With Marco

This video teaches the basics of linear regression, including theoretical concepts and hands-on examples in Python, to help viewers understand and apply linear regression in data science tasks.

Key Takeaways
  1. Estimate coefficients using linear regression
  2. Understand the error function
  3. Perform hypothesis testing for coefficients
  4. Assess the relevance of a linear model
  5. Apply linear regression concepts using Python code
  6. Use a GitHub notebook for hands-on examples
💡 Linear regression is a fundamental concept in machine learning and data science, and understanding its theoretical aspects and practical applications is crucial for working with data.

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