Complete Linear Regression Analysis in Python

 

Complete Linear Regression Analysis in Python

Linear Regression in Python| Simple Regression, Multiple Regression, Ridge Regression, Lasso and subset selection also

Sure! Here’s a brief guide on how to perform a complete linear regression analysis in Python:

1. Import the Required Libraries
2. Load the Dataset
3. Perform Exploratory Data Analysis
4. Visualizing the Data
5. Creating a Linear Regression Model
6. Testing the Linear Regression Model

You can find a detailed guide on how to perform these steps in Python on this blog or this guide.

I hope this helps! Let me know if you have any other questions.

What you'll learn

• Learn how to solve real life problem using the Linear Regression technique
• Preliminary analysis of data using Univariate and Bivariate analysis before running Linear regression
• Predict future outcomes basis past data by implementing Simplest Machine Learning algorithm
• 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
• Indepth knowledge of data collection and data preprocessing for Machine Learning Linear Regression problem
• Learn advanced variations of OLS method of Linear Regression
• Course contains a end-to-end DIY project to implement your learnings from the lectures
• How to convert business problem into a Machine learning Linear Regression problem
• Basic statistics using Numpy library in Python
• Data representation using Seaborn library in Python
• Linear Regression technique of Machine Learning using Scikit Learn and Statsmodel libraries of Python

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