Simple Regression & Multiple Regression| must-know for Machine Learning & Econometrics | Linear Regression in R studio
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
How to do basic statistical operations in R
Advanced Linear regression techniques using GLMNET package of R
Graphically representing data in R before and after analysis
Students will need to install R and R studio software but we have a separate lecture to help you install the same
You're looking for a complete Linear Regression course that teaches you everything you need to create a Linear Regression model in R, right?
You've found the right Linear Regression course!
After completing this course you will be able to:
· Identify the business problem which can be solved using linear regression technique of Machine Learning.
· Create a linear regression model in R and analyze its result.
· Confidently practice, discuss and understand Machine Learning concepts
A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning basics course.
Who this course is for:
People pursuing a career in data science
Working Professionals beginning their Data journey
Statisticians needing more practical experience
Anyone curious to master Linear Regression from beginner to advanced in short span of time