Building Sentiment Analysis Systems in Python

Building Sentiment Analysis Systems in Python course. This course teaches you how to build systems for sentiment analysis in text using the Python programming language. Nowadays, people express their opinions and thoughts in abundance online. Sentiment analysis helps us analyze these opinions and understand how people feel about a particular topic. In this course, you’ll learn how to extract sentiment from text using a variety of methods, including rule-based methods and machine learning.This training course introduces you to the principles of building systems for sentiment analysis in text. Using the Python programming language, you will be able to identify and categorize the emotions embedded in online comments. In this course, we will first examine the differences between methods based on predefined rules and machine learning methods in sentiment analysis. Then, we’ll build practical sentiment analyzers using powerful tools like VADER, Sentiwordnet, and NaiveBiz Classifiers. Next, we’ll hone our skills by applying these analytics to a real dataset of movie reviews. Finally, we will review the concept of support vector machines and examine the reasons for the preference of the Naive Bayes classifier in many sentiment analysis problems. By completing this course, you will gain a thorough understanding of the process of extracting sentiment from text and the factors influencing choosing the right method for each problem.