You're reading from Artificial Intelligence By Example Acquire advanced AI, machine learning, and deep learning design skills

Product type Paperback

Published in Feb 2020

Publisher Packt

ISBN-13 9781839211539

Length 578 pages

Edition 2nd Edition

Languages

Python

Tools

TensorFlow

Concepts

Artificial Intelligence

Author (1):

Denis Rothman

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Table of Contents (23) Chapters

Preface

1. Getting Started with Next-Generation Artificial Intelligence through Reinforcement Learning

2. Building a Reward Matrix – Designing Your Datasets FREE CHAPTER

3. Machine Intelligence – Evaluation Functions and Numerical Convergence

4. Optimizing Your Solutions with K-Means Clustering

5. How to Use Decision Trees to Enhance K-Means Clustering

6. Innovating AI with Google Translate

7. Optimizing Blockchains with Naive Bayes

8. Solving the XOR Problem with a Feedforward Neural Network

9. Abstract Image Classification with Convolutional Neural Networks (CNNs)

10. Conceptual Representation Learning

11. Combining Reinforcement Learning and Deep Learning

12. AI and the Internet of Things (IoT)

13. Visualizing Networks with TensorFlow 2.x and TensorBoard

14. Preparing the Input of Chatbots with Restricted Boltzmann Machines (RBMs) and Principal Component Analysis (PCA)

15. Setting Up a Cognitive NLP UI/CUI Chatbot

16. Improving the Emotional Intelligence Deficiencies of Chatbots

17. Genetic Algorithms in Hybrid Neural Networks

18. Neuromorphic Computing

19. Quantum Computing

20. Answers to the Questions

21. Other Books You May Enjoy

22. Index

Defining basic terms and goals

The goal of this chapter is to prepare data to create the input of a chatbot we will build in Chapter 15, Setting Up a Cognitive NLP UI/CUI Chatbot.

Creating a chatbot requires preparation. We cannot just step into a project without a minimum amount of information. In our case, we will examine a dataset I created based on movie preferences. I did not choose to download huge datasets because we need to first focus on understanding the process and building a model using basic data.

The size of the datasets increase daily on an online platform. When we watch a movie on a streaming platform, on Netflix for example, we can like the movie or click on the thumbs-down button.

When we approve or disapprove of a movie on an online platform, our preferences are recorded. The features of these movies provide valuable information for the platform, which can then display choices we prefer: action, adventure, romantic, comedy, and more.

In this...