Book Image

Building Natural Language Applications with TensorFlow [Video]

By : Kaiser Hamid Rabbi
Book Image

Building Natural Language Applications with TensorFlow [Video]

By: Kaiser Hamid Rabbi

Overview of this book

<p>Do you want your machine to analyze, understand, and generate human speech? Do you want to build chatbots? NLP is the next step in bridging many concerns that users, businesses, and developers experience with customer service.</p> <p>Chatbots are making it easier and replacing humans everywhere in social media, websites, stores, and even business-to-business conversations. With a less talk and more action approach, this course will lead you through various implementations of NLP techniques by implementing end-to-end deep learning models and creating an intelligent chatbot on our own.</p> <p>Get your hands on this course to learn the most fascinating technology in the field of AI and leverage the power of TensorFlow right away!</p> <p>The codes of this course can be found on GitHub:&nbsp;<a href="https://github.com/PacktPublishing/-Building-Natural-Language-Applications-with-TensorFlow" target="_blank">https://github.com/PacktPublishing/-Building-Natural-Language-Applications-with-TensorFlow</a></p> <h1>Style and Approach</h1> <p>This hands-on course covers all the important aspects of Natural Language Processing and Deep Learning models with TensorFlow. Throughout the course, you'll build an intelligent chatbot with step-by-step instructions to implement them following the intuition topics.</p>
Table of Contents (5 chapters)
Chapter 3
Build a Seq2Seq Model with Encoder and Decoder RNN
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Section 1
Create Placeholders for Inputs and Targets
First we will create placeholders for the inputs and the targets. Then we will preprocess the targets. - Create placeholders - Preprocess the targets