Home > Store

Artificial Intelligence for Business, 2nd Edition

eBook (Watermarked)

  • Your Price: $23.19
  • List Price: $28.99
  • Includes EPUB and PDF
  • About eBook Formats
  • This eBook includes the following formats, accessible from your Account page after purchase:

    ePub EPUB The open industry format known for its reflowable content and usability on supported mobile devices.

    Adobe Reader PDF The popular standard, used most often with the free Acrobat® Reader® software.

    This eBook requires no passwords or activation to read. We customize your eBook by discreetly watermarking it with your name, making it uniquely yours.

Also available in other formats.

Register your product to gain access to bonus material or receive a coupon.


  • Copyright 2021
  • Pages: 272
  • Edition: 2nd
  • eBook (Watermarked)
  • ISBN-10: 0-13-655658-2
  • ISBN-13: 978-0-13-655658-9

The Easy Introduction to Machine Learning (Ml) for Nontechnical People--In Business and Beyond

Artificial Intelligence for Business is your plain-English guide to Artificial Intelligence (AI) and Machine Learning (ML): how they work, what they can and cannot do, and how to start profiting from them. Writing for nontechnical executives and professionals, Doug Rose demystifies AI/ML technology with intuitive analogies and explanations honed through years of teaching and consulting. Rose explains everything from early expert systems to advanced deep learning networks.

First, Rose explains how AI and ML emerged, exploring pivotal early ideas that continue to influence the field. Next, he deepens your understanding of key ML concepts, showing how machines can create strategies and learn from mistakes. Then, Rose introduces current powerful neural networks: systems inspired by the structure and function of the human brain. He concludes by introducing leading AI applications, from automated customer interactions to event prediction. Throughout, Rose stays focused on business: applying these technologies to leverage new opportunities and solve real problems.

  • Compare the ways a machine can learn, and explore current leading ML algorithms
  • Start with the right problems, and avoid common AI/ML project mistakes
  • Use neural networks to automate decision-making and identify unexpected patterns
  • Help neural networks learn more quickly and effectively
  • Harness AI chatbots, virtual assistants, virtual agents, and conversational AI applications

Sample Content

Sample Pages

Download the sample pages (includes Chapter 1)

Table of Contents

Foreword     xv

Preface     xix

PART I:  Thinking Machines: An Overview of Artificial Intelligence     1

Chapter 1:  What Is Artificial Intelligence?     3

What Is Intelligence?     4

Testing Machine Intelligence     6

The General Problem Solver     8

Strong and Weak Artificial Intelligence     11

Artificial Intelligence Planning     14

Learning over Memorizing     15

Chapter Takeaways     18

Chapter 2:  The Rise of Machine Learning     19

Practical Applications of Machine Learning     22

Artificial Neural Networks     24

The Fall and Rise of the Perceptron     27

Big Data Arrives     30

Chapter Takeaways     33

Chapter 3:  Zeroing in on the Best Approach     35

Expert System Versus Machine Learning     35

Supervised Versus Unsupervised Learning     37

Backpropagation of Errors     38

Regression Analysis     41

Chapter Takeaways     43

Chapter 4:  Common AI Applications     45

Intelligent Robots     45

Natural Language Processing     48

The Internet of Things     50

Chapter Takeaways     51

Chapter 5:  Putting AI to Work on Big Data     53

Understanding the Concept of Big Data     54

Teaming Up with a Data Scientist     54

Machine Learning and Data Mining: What's the Difference?     55

Making the Leap from Data Mining to Machine Learning     56

Taking the Right Approach     57

Chapter Takeaways     59

Chapter 6:  Weighing Your Options     61

Chapter Takeaways     64

PART II:  Machine Learning     65

Chapter 7:  What Is Machine Learning?     67

How a Machine Learns     71

Working with Data     74

Applying Machine Learning     77

Different Types of Learning     79

Chapter Takeaways     81

Chapter 8:  Different Ways a Machine Learns     83

Supervised Machine Learning     83

Unsupervised Machine Learning     86

Semi-Supervised Machine Learning     89

Reinforcement Learning     91

Chapter Takeaways     93

Chapter 9:  Popular Machine Learning Algorithms     95

Decision Trees     99

k-Nearest Neighbor     101

k-Means Clustering     104

Regression Analysis     108

Naive Bayes     110

Chapter Takeaways     113

Chapter 10:  Applying Machine Learning Algorithms     115

Fitting the Model to Your Data     119

Choosing Algorithms     120

Ensemble Modeling     121

Deciding on a Machine Learning Approach     123

Chapter Takeaways     124

Chapter 11:  Words of Advice     125

Start Asking Questions     125

Don't Mix Training Data with Test Data     127

Don't Overstate a Model's Accuracy     127

Know Your Algorithms     128

Chapter Takeaways     128

PART III:  Artificial Neural Networks     129

Chapter 12:  What Are Artificial Neural Networks?     131

Why the Brain Analogy?     133

Just Another Amazing Algorithm     133

Getting to Know the Perceptron     135

Squeezing Down a Sigmoid Neuron     138

Adding Bias     141

Chapter Takeaways     142

Chapter 13:  Artificial Neural Networks in Action     143

Feeding Data into the Network     143

What Goes on in the Hidden Layers     145

Understanding Activation Functions     149

Adding Weights     151

Adding Bias     152

Chapter Takeaways     153

Chapter 14:  Letting Your Network Learn     155

Starting with Random Weights and Biases     156

Making Your Network Pay for Its Mistakes: The Cost Function     157

Combining the Cost Function with Gradient Descent     158

Using Backpropagation to Correct for Errors     160

Tuning Your Network     163

Employing the Chain Rule     164

Batching the Data Set with Stochastic Gradient Descent     166

Chapter Takeaways     167

Chapter 15:  Using Neural Networks to Classify or Cluster     169

Solving Classification Problems     170

Solving Clustering Problems     172

Chapter Takeaways     174

Chapter 16:  Key Challenges     175

Obtaining Enough Quality Data     175

Keeping Training and Test Data Separate     176

Carefully Choosing Your Training Data     177

Taking an Exploratory Approach     177

Choosing the Right Tool for the Job     178

Chapter Takeaways     178

PART IV:  Putting Artificial Intelligence to Work     179

Chapter 17:  Harnessing the Power of Natural Language Processing     181

Extracting Meaning from Text and Speech with NLU     183

Delivering Sensible Responses with NLG     184

Automating Customer Service     186

Reviewing the Top NLP Tools and Resources     187

NLU Tools     189

NLG Tools     190

Chapter Takeaways     191

Chapter 18:  Automating Customer Interactions     193

Choosing Natural Language Technologies     195

Review the Top Tools for Creating Chatbots and Virtual Agents     196

Chapter Takeaways     198

Chapter 19:  Improving Data-Based Decision-Making     199

Choosing Between Automated and Intuitive Decision-Making     201

Gathering Data in Real Time from IoT Devices     202

Reviewing Automated Decision-Making Tools     204

Chapter Takeaways     205

Chapter 20:  Using Machine Learning to Predict Events and Outcomes     207

Machine Learning Is Really about Labeling Data     208

Looking at What Machine Learning Can Do     210

Predict What Customers Will Buy     210

Answer Questions Before They're Asked     210

Make Better Decisions Faster     212

Replicate Expertise in Your Business     213

Use Your Power for Good, Not Evil: Machine Learning Ethics     214

Review the Top Machine Learning Tools     216

Chapter Takeaways     218

Chapter 21:  Building Artificial Minds     219

Separating Intelligence from Automation     221

Adding Layers for Deep Learning     222

Considering Applications for Artificial Neural Networks     223

Classifying Your Best Customers     224

Recommending Store Layouts     225

Analyzing and Tracking Biometrics     226

Reviewing the Top Deep Learning Tools     228

Chapter Takeaways     229

Index     231


Submit Errata

More Information

InformIT Promotional Mailings & Special Offers

I would like to receive exclusive offers and hear about products from InformIT and its family of brands. I can unsubscribe at any time.


Pearson Education, Inc., 221 River Street, Hoboken, New Jersey 07030, (Pearson) presents this site to provide information about products and services that can be purchased through this site.

This privacy notice provides an overview of our commitment to privacy and describes how we collect, protect, use and share personal information collected through this site. Please note that other Pearson websites and online products and services have their own separate privacy policies.

Collection and Use of Information

To conduct business and deliver products and services, Pearson collects and uses personal information in several ways in connection with this site, including:

Questions and Inquiries

For inquiries and questions, we collect the inquiry or question, together with name, contact details (email address, phone number and mailing address) and any other additional information voluntarily submitted to us through a Contact Us form or an email. We use this information to address the inquiry and respond to the question.

Online Store

For orders and purchases placed through our online store on this site, we collect order details, name, institution name and address (if applicable), email address, phone number, shipping and billing addresses, credit/debit card information, shipping options and any instructions. We use this information to complete transactions, fulfill orders, communicate with individuals placing orders or visiting the online store, and for related purposes.


Pearson may offer opportunities to provide feedback or participate in surveys, including surveys evaluating Pearson products, services or sites. Participation is voluntary. Pearson collects information requested in the survey questions and uses the information to evaluate, support, maintain and improve products, services or sites, develop new products and services, conduct educational research and for other purposes specified in the survey.

Contests and Drawings

Occasionally, we may sponsor a contest or drawing. Participation is optional. Pearson collects name, contact information and other information specified on the entry form for the contest or drawing to conduct the contest or drawing. Pearson may collect additional personal information from the winners of a contest or drawing in order to award the prize and for tax reporting purposes, as required by law.


If you have elected to receive email newsletters or promotional mailings and special offers but want to unsubscribe, simply email information@informit.com.

Service Announcements

On rare occasions it is necessary to send out a strictly service related announcement. For instance, if our service is temporarily suspended for maintenance we might send users an email. Generally, users may not opt-out of these communications, though they can deactivate their account information. However, these communications are not promotional in nature.

Customer Service

We communicate with users on a regular basis to provide requested services and in regard to issues relating to their account we reply via email or phone in accordance with the users' wishes when a user submits their information through our Contact Us form.

Other Collection and Use of Information

Application and System Logs

Pearson automatically collects log data to help ensure the delivery, availability and security of this site. Log data may include technical information about how a user or visitor connected to this site, such as browser type, type of computer/device, operating system, internet service provider and IP address. We use this information for support purposes and to monitor the health of the site, identify problems, improve service, detect unauthorized access and fraudulent activity, prevent and respond to security incidents and appropriately scale computing resources.

Web Analytics

Pearson may use third party web trend analytical services, including Google Analytics, to collect visitor information, such as IP addresses, browser types, referring pages, pages visited and time spent on a particular site. While these analytical services collect and report information on an anonymous basis, they may use cookies to gather web trend information. The information gathered may enable Pearson (but not the third party web trend services) to link information with application and system log data. Pearson uses this information for system administration and to identify problems, improve service, detect unauthorized access and fraudulent activity, prevent and respond to security incidents, appropriately scale computing resources and otherwise support and deliver this site and its services.

Cookies and Related Technologies

This site uses cookies and similar technologies to personalize content, measure traffic patterns, control security, track use and access of information on this site, and provide interest-based messages and advertising. Users can manage and block the use of cookies through their browser. Disabling or blocking certain cookies may limit the functionality of this site.

Do Not Track

This site currently does not respond to Do Not Track signals.


Pearson uses appropriate physical, administrative and technical security measures to protect personal information from unauthorized access, use and disclosure.


This site is not directed to children under the age of 13.


Pearson may send or direct marketing communications to users, provided that

  • Pearson will not use personal information collected or processed as a K-12 school service provider for the purpose of directed or targeted advertising.
  • Such marketing is consistent with applicable law and Pearson's legal obligations.
  • Pearson will not knowingly direct or send marketing communications to an individual who has expressed a preference not to receive marketing.
  • Where required by applicable law, express or implied consent to marketing exists and has not been withdrawn.

Pearson may provide personal information to a third party service provider on a restricted basis to provide marketing solely on behalf of Pearson or an affiliate or customer for whom Pearson is a service provider. Marketing preferences may be changed at any time.

Correcting/Updating Personal Information

If a user's personally identifiable information changes (such as your postal address or email address), we provide a way to correct or update that user's personal data provided to us. This can be done on the Account page. If a user no longer desires our service and desires to delete his or her account, please contact us at customer-service@informit.com and we will process the deletion of a user's account.


Users can always make an informed choice as to whether they should proceed with certain services offered by InformIT. If you choose to remove yourself from our mailing list(s) simply visit the following page and uncheck any communication you no longer want to receive: www.informit.com/u.aspx.

Sale of Personal Information

Pearson does not rent or sell personal information in exchange for any payment of money.

While Pearson does not sell personal information, as defined in Nevada law, Nevada residents may email a request for no sale of their personal information to NevadaDesignatedRequest@pearson.com.

Supplemental Privacy Statement for California Residents

California residents should read our Supplemental privacy statement for California residents in conjunction with this Privacy Notice. The Supplemental privacy statement for California residents explains Pearson's commitment to comply with California law and applies to personal information of California residents collected in connection with this site and the Services.

Sharing and Disclosure

Pearson may disclose personal information, as follows:

  • As required by law.
  • With the consent of the individual (or their parent, if the individual is a minor)
  • In response to a subpoena, court order or legal process, to the extent permitted or required by law
  • To protect the security and safety of individuals, data, assets and systems, consistent with applicable law
  • In connection the sale, joint venture or other transfer of some or all of its company or assets, subject to the provisions of this Privacy Notice
  • To investigate or address actual or suspected fraud or other illegal activities
  • To exercise its legal rights, including enforcement of the Terms of Use for this site or another contract
  • To affiliated Pearson companies and other companies and organizations who perform work for Pearson and are obligated to protect the privacy of personal information consistent with this Privacy Notice
  • To a school, organization, company or government agency, where Pearson collects or processes the personal information in a school setting or on behalf of such organization, company or government agency.


This web site contains links to other sites. Please be aware that we are not responsible for the privacy practices of such other sites. We encourage our users to be aware when they leave our site and to read the privacy statements of each and every web site that collects Personal Information. This privacy statement applies solely to information collected by this web site.

Requests and Contact

Please contact us about this Privacy Notice or if you have any requests or questions relating to the privacy of your personal information.

Changes to this Privacy Notice

We may revise this Privacy Notice through an updated posting. We will identify the effective date of the revision in the posting. Often, updates are made to provide greater clarity or to comply with changes in regulatory requirements. If the updates involve material changes to the collection, protection, use or disclosure of Personal Information, Pearson will provide notice of the change through a conspicuous notice on this site or other appropriate way. Continued use of the site after the effective date of a posted revision evidences acceptance. Please contact us if you have questions or concerns about the Privacy Notice or any objection to any revisions.

Last Update: November 17, 2020