Machine Learning

As per Wikipedia:

“Machine learning provides computers with the ability to learn without being explicitly programmed”

Machine learning in general comprises three major steps:

1. We collect a lot of examples that specify the correct output for a given input.
2. Based on the input dataset, we apply algorithms to form a model or a mathematical function that can predict the outcome.
3. We pass the input to the mathematical function obtained in step 2 to obtain the necessary results.  Consider the following diagram:

In this chapter, we will cover a simple experiment using Google’s Prediction API with Salesforce data, and, in the later chapters, we will introduce you to the PredictionIO part of Einstein offerings from Salesforce, which is an open source Machine Learning Server that allows developers and data scientists to capture data via its Event server, build predictive models with algorithms, and then deploy it as a web service.