3.1 Introduction to Natural Language Processing
This section provides an overview of natural language processing, covering the basics of text data, language models, and the applications of NLP in real-world scenarios.
3.2 Text Preprocessing Techniques
In this chapter, you will learn about the different techniques used to preprocess text data, including tokenization, stemming, and stop word removal. You will also explore the importance of data cleaning and normalization in NLP.
3.3 Text Classification and Sentiment Analysis
This chapter focuses on text classification and sentiment analysis, including the different algorithms used to classify text data into categories and determine the sentiment of a given text. You will also learn about the challenges and limitations of these techniques.
3.4 Language Translation and Generation
In this section, you will explore the techniques used for language translation and generation, including machine translation and text summarization. You will also learn about the challenges and limitations of these techniques and their applications in real-world scenarios.