Book Image

Keras 2.x Projects

By : John Bura
Book Image

Keras 2.x Projects

By: John Bura

Overview of this book

Keras is a Python library that provides a simple and clean way to create a range of deep learning models. This course introduces you to Keras and shows you how to create applications with maximum readability. You take your first steps by getting introduced to Keras, its benefits, and its applications. As you get comfortable with Keras, you will learn how to predict business outcomes using time series data and various forecasting techniques. By learning the basic concepts of reinforcement learning, you will be able to create algorithms that can learn and adapt to environmental changes and control your robots. Then, you will learn various natural language processing techniques and use the Natural Language Toolkit to analyze, classify, and tag text. By the end of the course, you’ll have the skills and the confidence to work on existing deep learning projects or create your own applications. The code bundle for this course can be downloaded from here: https://github.com/TrainingByPackt/Keras-2.X-Projects-eLearning
Table of Contents (4 chapters)
Chapter 4
Reuters Newswire Topics Classifier in Keras
Content Locked
Section 3
Sentiment Analysis
The term sentiment analysis refers to the set of natural language processing techniques, text analysis, and computational linguistics to identify and extract subjective information in written or spoken text sources. If this subjective information is taken from large amounts of data, and therefore from the opinions of large groups of people, the sentiment analysis can also be called opinion mining. Here are the topics that we will cover now: - Sentiment Analysis - NLP Methods - Sentence Splitting - Tokenization - Part-of-Speech (PoS) Tagging - Shallow Parsing - Named Entity Recognition - Syntactic Parsing