The journey of learning Python programming and implementing Artificial Intelligence started with this series of tutorials and case studies. This is now the final project of the series and we will be covering all the key topics we learnt so far. Starting from Data Preprocessing, to turning text into features, performing NLP on real news articles, and then building a Machine Learning model to predict classes of output. The primary aim of this series has been to practice Python programming, learn concepts within Python that help in performing AI tasks like Machine Learning, Speech Processing, NLP, Cognitive Science, etc. From starting with statistical concepts to building ML models, we have covered all these bases in the last twelve chapters. In this chapter, we will implement a final project using all the concepts we have learnt throughout this series.  

Machine Learning Natural Language Processing Python and AI Sentiment Analysis

In the last seven chapters, we have explored concepts ranging from the basics of Python Programming, implementation of mathematics in the code and machine learning. To move to the next concept within Artificial Intelligence, we will be looking at executing Logic Programming learned in the previous chapter and work on Natural Language Processing. NLP is a complex suite within AI that deals with languages and is integral to multiple real-world projects in various industries.

Natural Language Processing NLP Python

This chapter will show the implementation of Natural Language Processing through a case study that deals with sentiments among flight travelers. In the first case study, we built a machine learning pipeline that ran through data acquiring to performing predictions. In this analysis, we will be presenting the same pipeline and adding an additional step to work with textual data. We will also be using the libraries talked about in the previous chapter and learn concepts of vectorizing text data to numerical data. The aim of Natural Language Processing (NLP) is to work with textual (string–based) data and perform analysis on it. In this chapter, we will focus on making predictions and building categorizations from input feeds of data.

AI Artificial Intelligence Natural Language Processing NLP Python