In this chapter, we will go through several sample machine learning (ML) exercises using the IBM Cloud platform to uncover the power of the Python language as the machine learning programming language of choice, and to look at the Machine Learning service offered by IBM Watson Studio.

This chapter will enable you to understand the practice of proper feature engineering as well as demonstrate the ability to run supervised (classification) and unsupervised (clustering) algorithms in the IBM Cloud, using IBM Watson Studio.

With simple practice examples, this chapter will guide you through the steps for implementing various machine learning projects using IBM Watson Studio.

We will break down this chapter into the following areas:

• Watson Studio and Python
• Data cleansing and preparation
• A k-means clustering example
• A k-nearest neighbors example
• A time series prediction example