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