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 2
Natural Language Processing
Natural language processing (NLP) is the process of automatic processing of information written or spoken in a natural language using an electronic calculator. This is made particularly difficult and complex due to the intrinsic characteristics of the ambiguity of human language. When it's necessary to make the machine learn methods of interaction with the environment typical of man, the question isn't so much that of storing data, but that of letting the machine learn how this data can be translated simultaneously to create a concept. Natural language interacts with the environment generating predictive knowledge. Here are the topics that we will cover now: - Natural Language Processing (NLP) - Robot Control Overview - NLP Phases - Morphology Analysis - Syntax Analysis - Semantic Analysis - Pragmatic Analysis - Automatic Processing Problems - NLP Applications - Information Retrieval (IR) - Information Extraction (IE) - Question-Answering (QA) - Automatic Summarization - Automatic Translation - Automatic Translation Types