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Artificial Intelligence By Example

Artificial Intelligence By Example - Second Edition

By : Denis Rothman
4.6 (17)
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Artificial Intelligence By Example

Artificial Intelligence By Example

4.6 (17)
By: Denis Rothman

Overview of this book

AI has the potential to replicate humans in every field. Artificial Intelligence By Example, Second Edition serves as a starting point for you to understand how AI is built, with the help of intriguing and exciting examples. This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from computer programs such as a simple chess engine to cognitive chatbots, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and Internet of Things (IoT), and develop emotional quotient in chatbots using neural networks such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs). This edition also has new examples for hybrid neural networks, combining reinforcement learning (RL) and deep learning (DL), chained algorithms, combining unsupervised learning with decision trees, random forests, combining DL and genetic algorithms, conversational user interfaces (CUI) for chatbots, neuromorphic computing, and quantum computing. By the end of this book, you will understand the fundamentals of AI and have worked through a number of examples that will help you develop your AI solutions.
Table of Contents (23 chapters)
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21
Other Books You May Enjoy
22
Index

Dataset optimization and control

At one point, a manager or customer will inevitably ask an AI expert about the exact data required for an ML project, and in which format it's needed. Providing an answer will take some hard thinking and work.

One might wonder why the data is not open, like when we download ready-to-use datasets to learn AI algorithms. In corporate life, there are security rules and processes. Often the data required is on one or more servers. You will not be granted permission to do anything you want. You will have to specify your needs and requests. Obtaining data in the way required for AI comes at a cost for a corporation. You will have to justify your requests.

Start by properly designing the dataset and choosing the right ML model. The dataset and ML model will fit the fundamental requirement to optimize AGV distances. Each AGV in a given warehouse must reduce the distance it takes to go from a pier (where boats might drop off...

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Artificial Intelligence By Example
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