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Anthony So - The Applied Artificial Intelligence Workshop: Start working with AI today, to build games, design decision trees, and train your own machine learning models

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With knowledge and information shared by experts, take your first steps towards creating scalable AI algorithms and solutions in Python, through practical exercises and engaging activities

Key Features
  • Learn about AI and ML algorithms from the perspective of a seasoned data scientist
  • Get practical experience in ML algorithms, such as regression, tree algorithms, clustering, and more
  • Design neural networks that emulate the human brain
Book Description

You already know that artificial intelligence (AI) and machine learning (ML) are present in many of the tools you use in your daily routine. But do you want to be able to create your own AI and ML models and develop your skills in these domains to kickstart your AI career?

The Applied Artificial Intelligence Workshop gets you started with applying AI with the help of practical exercises and useful examples, all put together cleverly to help you gain the skills to transform your career.

The book begins by teaching you how to predict outcomes using regression. Youll then learn how to classify data using techniques such as k-nearest neighbor (KNN) and support vector machine (SVM) classifiers. As you progress, youll explore various decision trees by learning how to build a reliable decision tree model that can help your company find cars that clients are likely to buy. The final chapters will introduce you to deep learning and neural networks. Through various activities, such as predicting stock prices and recognizing handwritten digits, youll learn how to train and implement convolutional neural networks (CNNs) and recurrent neural networks (RNNs).

By the end of this applied AI book, youll have learned how to predict outcomes and train neural networks and be able to use various techniques to develop AI and ML models.

What you will learn
  • Create your first AI game in Python with the minmax algorithm
  • Implement regression techniques to simplify real-world data
  • Experiment with classification techniques to label real-world data
  • Perform predictive analysis in Python using decision trees and random forests
  • Use clustering algorithms to group data without manual support
  • Learn how to use neural networks to process and classify labeled images
Who this book is for

The Applied Artificial Intelligence Workshop is designed for software developers and data scientists who want to enrich their projects with machine learning. Although you do not need any prior experience in AI, it is recommended that you have knowledge of high school-level mathematics and at least one programming language, preferably Python. Although this is a beginners book, experienced students and programmers can improve their Python skills by implementing the practical applications given in this book.

Table of Contents
  1. Introduction to Artificial Intelligence
  2. An Introduction to Regression
  3. An Introduction to Classification
  4. An Introduction to Decision Trees
  5. Artificial Intelligence: Clustering
  6. Neural Networks and Deep Learning

Anthony So: author's other books


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The
Applied
Artificial
Intelligence
Workshop

Start working with AI today, to build games, design decision trees, and train your own machine learning models

Anthony So, William So, and Zsolt Nagy

The Applied Artificial Intelligence Workshop

Copyright 2020 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Authors: Anthony So, William So, and Zsolt Nagy

Reviewers: Swanand Bagve, John Wesley Doyle, Ashish Pratik Patil, Shantanu Shivrup Pathak, and Subhranil Roy

Managing Editor: Adrian Cardoza

Acquisitions Editors: Manuraj Nair, Sneha Shinde, Anindya Sil, and Karan Wadekar

Production Editor: Salma Patel

Editorial Board: Megan Carlisle, Samuel Christa, Mahesh Dhyani, Heather Gopsill, Manasa Kumar, Alex Mazonowicz, Monesh Mirpuri, Bridget Neale, Dominic Pereira, Shiny Poojary, Abhishek Rane, Brendan Rodrigues, Erol Staveley, Ankita Thakur, Nitesh Thakur, and Jonathan Wray

First published: July 2020

Production reference: 1200720

ISBN: 978-1-80020-581-9

Published by Packt Publishing Ltd.

Livery Place, 35 Livery Street

Birmingham B3 2PB, UK

Table of Contents
Preface
About the Book

You already know that Artificial Intelligence (AI) and Machine Learning (ML) are present in many of the tools you use in your daily routine. But do you want to be able to create your own AI and ML models and develop your skills in these domains to kickstart your AI career?

The Applied Artificial Intelligence Workshop gets you started with applying AI with the help of practical exercises and useful examples, all put together cleverly to help you gain the skills to transform your career.

The book begins by teaching you how to predict outcomes using regression. You'll then learn how to classify data using techniques such as K-Nearest Nneighbor (KNN) and Support Vector Machine (SVM) classifiers. As you progress, you'll explore various decision trees by learning how to build a reliable decision tree model that can help your company find cars that clients are likely to buy. The final chapters will introduce you to deep learning and neural networks. Through various activities, such as predicting stock prices and recognizing handwritten digits, you'll learn how to train and implement

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