This chapter introduces algorithms for natural language processing (NLP). This chapter proceeds from the theoretical to the practical in a progressive manner. It will first introduce the fundamentals of NLP, followed by the basic algorithms. Then, it will look at one of the most popular neural networks that is widely used to design and implement solutions for important use cases for textual data. We will then look at the limitations of NLP before finally learning how we can use NLP to train a machine learning model that can predict the polarity of movie reviews.

This chapter will consist of the following sections: 

• Introducing NLP
• Bag-of-words-based (BoW-based) NLP
• Introduction to word embedding
• Use of recurrent neural networks for NLP
• Using NLP for sentiment analysis
• Case study: movie review sentiment analysis

By the end of this chapter, you will understand the basic techniques that are used for NLP. You should be able to understand how NLP can be used to solve some interesting real-world problems.

Let's start with the basic concepts.