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Artificial Intelligence By Example

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

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781839211539
Length 578 pages
Edition 2nd Edition
Languages
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Author (1):
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Denis Rothman Denis Rothman
Author Profile Icon Denis Rothman
Denis Rothman
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Table of Contents (23) Chapters Close

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

AI as a new frontier

Google has a great, but limited, translation program. Use the flaws to innovate! AI research and development has just scratched the surface of the innovations to come.

First, implement an AI solution. Then, use it for what it is. But don't accept its limits. Don't be negative about it. Innovate! Imagine ideas or listen to other ideas you like and build solutions in a team! Google might even publish your solutions!

Improving Google Translate for any translation is impossible. A realistic approach is to focus on customizing Google Translate for a given domain, such as the transportation company in this example. In the next section, we will focus on ways to customize Google Translate.

Lexical field and polysemy

Google_Translate_Customized.py will provide ideas on how to improve Google Translate in a specific area. This section focuses on the transportation vocabulary error Google Translate made. Once again, Google may rapidly correct...

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