Summary

In this chapter, you learned regression analysis-based machine learning and, in particular, how to implement linear and logistic regression models using Mahout, R, Python, Julia, and Spark. Additionally, we covered other related concepts of statistics such as variance, covariance, and ANOVA among others. We covered regression models in depth with examples to understand how to apply them to real-world problems. In the next chapter, we will cover deep learning methods.