Practical Linear Regression in R - Hands-On

This course teaches you about the most common & popular technique used in Data Science & Machine Learning: Linear Regression. You will learn the theory as well as applications of different types of linear regression models. At the end of the course, you will completely understand and know how to apply & implement in R linear models, how to run model's diagnostics, and how to know if the model is the best fit for your data, how to check the model's performance and to make predictions.

Linear regression is the simplest machine learning (and thus deep learning) model you can learn, yet there is so much depth that you'll be returning to it for years to come. That's why it's a great introductory course if you're interested in taking your first steps in the fields of:

• machine learning
• deep learning
• data science
• statistics

THIS COURSE HAS 5 SECTIONS COVERING EVERY ASPECT OF LINEAR REGRESSION: BOTH THEORY TO PRACTICE

• Fully understand the basics of Machine Learning & Linear Regression Models from theory to practice
• Harness applications of linear regression modeling in R
• Learn how to apply correctly linear regression models and test them in R
• Complete programming & data science exercises and an independent project in R
• Learn how to test the model's fit, how to select the most suitable linear models for your data, and make predictions
• Learn different types of linear regressions (1-dimensional and multi-dimensional models, logistic regressions, ANCOVA, etc)
• Learn how to deal with the categorical data in your regression modeling and correlation between variables
• Learn the basics of R-programming
• Get a copy of all scripts used in the course
• and MORE