Machine Learning Python: Regression Modeling

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Use Linear Regression to solve business problems and master the basics of Machine Learning

The course "Machine Learning Basics: Building Regression Model in Python" teaches you all the steps of creating a Linear Regression model, which is the most popular Machine Learning model, to solve business problems.

In this course students will learn the following:

  • How to predict future outcomes basis past data by implementing Simplest Machine Learning algorithm
  • How to do preliminary analysis of data using Univariate and Bivariate analysis before running Linear regression
  • Understand how to interpret the result of Linear Regression model and translate them into actionable insight
  • Understanding of basics of statistics and concepts of Machine Learning
  • Learn advanced variations of OLS method of Linear Regression
  • Linear Regression technique of Machine Learning using Scikit Learn and Statsmodel libraries of Python

This course is suitable for anyone curious about machine learning or professionals beginning their data journey.

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Basic knowledge

  • Students will need to install Python and Anaconda software but we have a separate lecture to help you install the same

What will you learn

In this course students will learn the following:

  • How to predict future outcomes basis past data by implementing Simplest Machine Learning algorithm
  • How to do preliminary analysis of data using Univariate and Bivariate analysis before running Linear regression
  • Understand how to interpret the result of Linear Regression model and translate them into actionable insight
  • Understanding of basics of statistics and concepts of Machine Learning
  • Learn advanced variations of OLS method of Linear Regression
  • Linear Regression technique of Machine Learning using Scikit Learn and Statsmodel libraries of Python
No sub-Tutorials exists in this Tutorial.
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