Machine learning is a stream of engineering which uses mathematics to allow machines to make classifications, predictions, recommendations, and so on, based on the data provided to them. This area is vast, and we could spend years discussing it. But in order to keep our discussion focused, we will discuss only what is required for the scope of this book.
Very broadly, machine learning can be divided into three big categories:
Supervised learning
Unsupervised learning
Semi supervised learning
The preceding diagram shows a broad classification of machine learning algorithms. Now let's discuss these in detail.
In supervised learning, we are generally given an input dataset, which is a historical record of actual events. We are also given what the expected output should look like. Using the historical data, we choose which factors contributed to the results. Such attributes are called features. Using the historical data, we understand how the previous results...