Summary
This was a chapter about textual analysis. We learned that it's a best practice in textual analysis to get rid of stopwords.
In the bag-of-words model, we used a document to create a bag containing words found in that same document. We learned how to build a feature vector for each document using all the word counts.
Classification algorithms are a type of machine learning algorithm, which involve determining the class of a given item. Naive Bayes classification is a probabilistic algorithm based on the Bayes theorem from probability theory and statistics. The Bayes theorem states that the posterior probability is proportional to the prior probability multiplied by the likelihood.
The next chapter will describe machine learning in more detail. Machine learning is a research field that shows a lot of promise. One day, it may even replace human labor completely. We will explore what we can do with scikit-learn, the Python machine learning package, using weather data as an example...
