Summary

Machine learning adoption has increased in leaps and bounds in the last few years. Availability of data in the digital age, scalable platforms to process large amount of data, focus on intelligent applications, and the realization of the business values of machine learning has driven the growth. Machine learning is a vast field that requires continuing education to gain expertise. This chapter has introduced a few important concepts in machine learning but the knowledge gained is just the tip of the iceberg. I would encourage the reader to keep exploring and augmenting their knowledge. In the next chapter, we will discuss one of the first and most important parts of a machine learning project, feature engineering. Feature engineering deals with transforming and presenting data to the learning algorithm. We will cover some common techniques for feature extraction and dimensionality reduction.