40,81 €
Mehr erfahren.
- Herausgeber: Packt Publishing
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Incorporate intelligence to your data-driven business insights and high accuracy business solutions
Key Features
- Explore IBM Watson capabilities such as Natural Language Processing (NLP) and machine learning
- Build projects to adopt IBM Watson across retail, banking, and healthcare
- Learn forecasting, anomaly detection, and pattern recognition with ML techniques
Book Description
IBM Watson provides fast, intelligent insight in ways that the human brain simply can't match. Through eight varied projects, this book will help you explore the computing and analytical capabilities of IBM Watson.
The book begins by refreshing your knowledge of IBM Watson's basic data preparation capabilities, such as adding and exploring data to prepare it for being applied to models. The projects covered in this book can be developed for different industries, including banking, healthcare, media, and security. These projects will enable you to develop an AI mindset and guide you in developing smart data-driven projects, including automating supply chains, analyzing sentiment in social media datasets, and developing personalized recommendations.
By the end of this book, you'll have learned how to develop solutions for process automation, and you'll be able to make better data-driven decisions to deliver an excellent customer experience.
What you will learn
- Build a smart dialog system with cognitive assistance solutions
- Design a text categorization model and perform sentiment analysis on social media datasets
- Develop a pattern recognition application and identify data irregularities smartly
- Analyze trip logs from a driving services company to determine profit
- Provide insights into an organization's supply chain data and processes
- Create personalized recommendations for retail chains and outlets
- Test forecasting effectiveness for better sales prediction strategies
Who this book is for
This book is for data scientists, AI engineers, NLP engineers, machine learning engineers, and data analysts who wish to build next-generation analytics applications. Basic familiarity with cognitive computing and sound knowledge of any programming language is all you need to understand the projects covered in this book.
Das E-Book können Sie in Legimi-Apps oder einer beliebigen App lesen, die das folgende Format unterstützen:
Seitenzahl: 246
Veröffentlichungsjahr: 2018
Ähnliche
IBM Watson Projects
Copyright © 2018 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 author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been 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.
Commissioning Editor: Pravin DhandreAcquisition Editor: Tushar GuptaContent Development Editor: Snehal KolteTechnical Editor: Dharmendra YadavCopy Editor: Safis EditingProject Coordinator: Manthan PatelProofreader: Safis EditingIndexer:Pratik ShirodkarGraphics: Jisha ChirayilProduction Coordinator:Arvindkumar Gupta
First published: September 2018
Production reference: 1290918
Published by Packt Publishing Ltd. Livery Place 35 Livery Street Birmingham B3 2PB, UK.
ISBN 978-1-78934-371-7
www.packtpub.com
Mapt is an online digital library that gives you full access to over 5,000 books and videos, as well as industry leading tools to help you plan your personal development and advance your career. For more information, please visit our website.
Why subscribe?
Spend less time learning and more time coding with practical eBooks and Videos from over 4,000 industry professionals
Improve your learning with Skill Plans built especially for you
Get a free eBook or video every month
Mapt is fully searchable
Copy and paste, print, and bookmark content
Packt.com
Did you know that Packt offers eBook versions of every book published, with PDF and ePub files available? You can upgrade to the eBook version at www.packt.com and as a print book customer, you are entitled to a discount on the eBook copy. Get in touch with us at [email protected] for more details.
At www.packt.com, you can also read a collection of free technical articles, sign up for a range of free newsletters, and receive exclusive discounts and offers on Packt books and eBooks.
Contributors
About the author
James Miller is an innovator and accomplished Sr. Project Lead and Solution Architect with 37 years experience. of extensive design and development across multiple platforms and technologies. Roles include leveraging his consulting experience to provide hands-on leadership in all phases of advanced analytics and related technology projects, providing recommendations for process improvement, report accuracy, adoption of disruptive technologies, enablement, and insight identification. Author: Statistics for Data Science, Mastering Predictive Analytics w/R, Big Data Visualization, Learning Watson Analytics, Implementing Splunk, Mastering Splunk, 5 Guiding Principles of a Successful Center of Excellence, and TM1 Developer's Certification Guide.
About the reviewer
Mayur Ravindra Narkhede has a good blend of experience in data science and industrial domain. He is a researcher with a B.Tech in computer science and an M.Tech in CSE with a specialization in Artificial Intelligence.
A data scientist whose core experience lies in building automated end-to-end solutions, he is proficient at applying technology, AI, ML, data mining, and design thinking to better understand and predict improvements in business functions and desirable requirements with growth profitability.
He has worked on multiple advanced solutions, such as ML and predictive model development for the oil and gas industry, financial services, road traffic and transport, life sciences, and the big data platform for asset-intensive industries.
Packt is searching for authors like you
If you're interested in becoming an author for Packt, please visit authors.packtpub.com and apply today. We have worked with thousands of developers and tech professionals, just like you, to help them share their insight with the global tech community. You can make a general application, apply for a specific hot topic that we are recruiting an author for, or submit your own idea.
Table of Contents
Title Page
Copyright and Credits
IBM Watson Projects
Packt Upsell
Why subscribe?
Packt.com
Contributors
About the author
About the reviewer
Packt is searching for authors like you
Preface
Who this book is for
What this book covers
To get the most out of this book
Download the example code files
Conventions used
Get in touch
Reviews
The Essentials of IBM Watson
Definition and objectives
IBM Cloud prerequisites
Exploring the Watson interface
The menu bar
Menu icon
IBM Cloud
Catalog
Docs
Support
Manage
Profile – avatar
Online glossary, let's chat, and feedback
What about Watson?
The Watson dashboard
Menu bar
Quick start information bar
Search, add, filter, and sort
Content panel area
Basic tasks refresher
The first step
Explore
Watson prompts
Predict
Assemble
Social media
Refine
Saving the original
Add – some data
Refine
Summary
A Basic Watson Project
The problem defined
Getting started
Gathering data
Building your Watson project
Loading your data
Data review
What does this mean?
Improving your score with Refine
Refine or Explore
Creating a prediction
Top predictors
Main Insight page
Details page
An insight
Reviewing the results
Summary
An Automated Supply Chain Scenario
The problem defined
Getting started
Gathering and reviewing  data
Building the Watson project
Loading your data
Reviewing the data
Refining the data
Creating a prediction
Supply chain prediction
Predictors
Main insights
Reviewing the results
Sharing with a dashboard
Adding a new visualization
Summary
Healthcare Dialoguing
The problem defined
What is dialoguing?
Leveraging (new) data to identify risk
Getting started
Gathering and reviewing data
Building the project
Reviewing the results
Exploring the dialog data
Collecting the data
Moving on
Recap
Results
Data quality of the prediction
Data quality report
More predictive strength
More detail
Assembling a story
Testing your story
Summary
Social Media Sentiment Analysis
The problem defined
Social media and IBM Watson Analytics
Getting started
Creating a Watson Analytics social media project
Building the project
Project creation step by step
Adding topics
Social media investigative themes
Adding dates
Languages
Sources
Reviewing the results
Deeper dive – conversation clusters
Navigation
Topics
Another look
Sentiment
Sentiment terms
Geography
Sources and sites
Influential authors
Author interests
Games and shopping 
Behavior
Demographics
The sentiment dictionary
The data
Summary
Pattern Recognition and Classification
The problem defined
Data peeking
Starting a pattern recognition and classification project
Investigation
Coach me
More with Watson Analytics
The insight bar
Modifying a visualization
Additional filtering
Item-based calculations
Navigate
Compare
Simply trending
Developing the pattern recognition and classification project
Quality
The Watson Analytics data quality report
Creating the prediction
The prediction workflow
Understanding the workflow step by step
Reviewing the results
Displaying top predictors and predictive strength
Summary
Retail and Personalized Recommendations
The problem defined
Product recommendation engines
Recommendations from Watson Analytics
The data at a glance
Starting the project
Range filter
Save me
Developing the project
Reviewing the results
Targets
Summary ribbon
The top predictors
Sharing the insights
Summary
Integration for Sales Forecasting
The problem defined
Product forecasting
Systematic forecasting
IBM Planning Analytics
Our data
Creating the forecast
Starting the project
Developing the project
Visualizations and data requirements
More questioning
Time Series
Other visualization options
Reviewing the results
Summary
Anomaly Detection in Banking Using AI
Defining the problem
Banking use cases
Corruption
Cash
Billing
Check tampering
Skimming
Larceny
Financial statement fraud
Starting the project
The data
Developing the project
The first question
Using Excel for sorting and filtering the data
Back to Watson
Check numbers
Reviewing the results
Collecting
Telling the story
Summary
What's Next
Chapter-by-chapter summary
Chapter 1 – The Essentials of IBM Watson
Chapter 2 – A Basic Watson Project
Chapter 3 – An Automated Supply Chain Scenario
Chapter 4 – Healthcare Dialoguing
Chapter 5 – Social Media Sentiment Analysis
Chapter 6 – Pattern Recognition And Classification
Chapter 7 – Retail And Personalized Recommendations
Chapter 8 – Integration for Sales Forecasting
Chapter 9 – Anomaly Detection in Banking With AI
Suggested next steps
Packt Publishing books, blogs, and video courses
Learning IBM Watson Analytics
LinkedIn groups
Product documentation
IBM websites
Experiment
Summary
Other Books You May Enjoy
Leave a review - let other readers know what you think
Preface
IBM Watson provides fast, intelligent insight in ways that the human brain simply can't match. Through eight different projects, this book helps you to explore the computing and analytical capabilities of IBM Watson.
The book begins by refreshing your knowledge of IBM Watson's basic data preparation capabilities, such as adding and exploring data to prepare it for being applied to models. The projects covered in this book can be developed for different industries, such as banking, healthcare, the media, and security. These projects will enable you to develop an AI mindset and guide you in developing smart data-driven projects, including automating supply chains, analyzing sentiment in social media datasets, and developing personalized recommendations.
By the end of this book, you'll have learned how to develop solutions for process automation, and you'll be able to make better data-driven decisions to deliver an excellent customer experience.
Who this book is for
This book is for data scientists, AI engineers, NLP engineers, machine learning engineers, and data analysts who wish to build next-generation analytics applications. Basic familiarity with cognitive computing and sound knowledge of any programming language is all you need to understand the projects covered in this book.
What this book covers
Chapter 1, The Essentials of IBM Watson, defines the latest version of (IBM) Watson Analytics and outlines various uses of the tool. In addition, the chapter provides an overview of Watson's interface and its major components, as well as offering a refresher on basic tasks such as adding data, exploring data, and creating a prediction.
Chapter 2, A Basic Watson Project, analyzes trip logs from a driving services company to determine which trip characteristics have a direct effect on a trip's profitability, what type of trip is most profitable, and which are prone to complications. This first project serves to cover the basics of a simple Watson project, preparing the reader for the upcoming, more complex projects presented in the following chapters.
Chapter 3, An Automated Supply Chain Scenario, consists of a use case project that focuses on analyzing how effective a supply chain is for a retail department store. This automated supply chain scenario provides insights into an organization's supply chain data and processes, in an attempt to isolate the cause of poor delivery performance.
Chapter 4, Healthcare Dialoguing, analyzes Watson's cognitive assistance solution, specifically with regard to creating an engaging dialog between healthcare providers and their patients. This project establishes relevant recommendations based upon patient inputs.
Chapter 5, Social Media Sentiment Analysis, tackles sentimental analysis using Watson to automatically analyze and categorize text posted to social media in an attempt to determine an audience's feeling about a topic.
Chapter 6, Pattern Recognition and Classification, discusses pattern recognition and using Watson to identify regularities in data in an effort to automatically classify athletes positionally based upon data provided.
Chapter 7, Retail and Personalized Recommendations, introduces the concept of personalized recommendations and the use of Watson to create a specialized plan through conversion. In this project, the objective is to create an individualized plan based upon characteristics found within a pool of data.
Chapter 8, Integration for Sales Forecasting, discusses integrating Watson with an organization's forecasting system in order to test its product sales forecasting effectiveness, comparing forecasts to actual results.
Chapter 9, Anomaly Detection in Banking with AI, uses Artificial Intelligence (AI) from a Watson perspective, walking through an example use case project related to the banking industry, in which transactions are evaluated to identify fraud.
Chapter 10, What's Next?, summarizes what readers have learned in the preceding chapters and what they can do next to continue the Watson learning process.
To get the most out of this book
Basic familiarity with cognitive computing and sound knowledge of any programming language is all you need to understand the projects covered in this book.
Download the example code files
You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packt.com/support and register to have the files emailed directly to you.
You can download the code files by following these steps:
Log in or register at
www.packt.com
.
Select the
SUPPORT
tab.
Click on
Code Downloads & Errata
.
Enter the name of the book in the
Search
box and follow the onscreen instructions.
Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:
WinRAR/7-Zip for Windows
Zipeg/iZip/UnRarX for Mac
7-Zip/PeaZip for Linux
The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/IBM-Watson-Project. In case there's an update to the code, it will be updated on the existing GitHub repository.
We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!
Conventions used
There are a number of text conventions used throughout this book.
CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "we can locate and select our SuperSupplyChain file."
Bold: Indicates a new term, an important word, or words that you see on screen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: The information box shows that Guide is the strongest predictor of TipGrade.
Get in touch
Feedback from our readers is always welcome.
General feedback: If you have questions about any aspect of this book, mention the book title in the subject of your message and email us at [email protected].
Errata: Although we have taken every care to ensure the accuracy of our content, mistakes do happen. If you have found a mistake in this book, we would be grateful if you would report this to us. Please visit www.packt.com/submit-errata, selecting your book, clicking on the Errata Submission Form link, and entering the details.
Piracy: If you come across any illegal copies of our works in any form on the Internet, we would be grateful if you would provide us with the location address or website name. Please contact us at [email protected] with a link to the material.
If you are interested in becoming an author: If there is a topic that you have expertise in and you are interested in either writing or contributing to a book, please visit authors.packtpub.com.
Reviews
Please leave a review. Once you have read and used this book, why not leave a review on the site that you purchased it from? Potential readers can then see and use your unbiased opinion to make purchase decisions, we at Packt can understand what you think about our products, and our authors can see your feedback on their book. Thank you!
For more information about Packt, please visit packt.com.
The Essentials of IBM Watson
IBM Watson Analytics brings smart data analysis and visualization, guided data discovery, automated predictive analytics, and cognitive capabilities to you as a service.
Through the process of making a project, this book attempts to help developers and business users alike learn the various computing and analytical capabilities of IBM Watson Analytics.
This book looks at each and every capability of the IBM Watson Analytics platform, such as speeding up predictive analytics for better business insights, building tailored interactions for an improved customer experience, identifying trends, investigating potential issues, and so on, thereby allowing readers to start building projects in their business context using Watson Analytics.
By the end of this book, you should be ready to use Watson Analytics to make better data-driven decisions, as well as visualize and communicate any analysis of your data that you might gain using Watson Analytics.
In this first chapter, we will try to define the latest version of IBM Watson Analytics and look at the various objectives of the tool. In addition, this chapter will provide an overview of Watson's interface, as well its major components, to offer a refresher on some basic tasks, such as adding data, exploring data, and creating a prediction.
This chapter will cover the following topics:
Definition and objectives
Exploring the Watson interface
A refresher of the basic tasks
Definition and objectives
Here's an interesting factoid—IBM Watson was named after IBM's first CEO and industrialist Thomas J. Watson (who has been credited with developing IBM's management style and corporate culture), and was specifically developed to answer questions on the quiz show Jeopardy!
IBM Watson has been described as a computer system that is based on cognitive computing and that, conceptually, can deliver answers to your questions.
Now the term cognitive also has an interesting definition. It is defined as being concerned with the act or process of knowing, or perceiving, which, as you can imagine, is enormously valuable to any business.
Cognitive algorithms have the ability to create insights and make evidence-based decisions in ambiguous circumstances, based upon as much data as possible.
IBM Watson is exciting because it attempts (in much the same way as a human would) to review the provided raw data and reason out an answer. In fact, Watson yields more of a hypothesis than an answer (based upon both the data and other dependencies or circumstances).
The concept of answering with a best-suited answer rather than simply providing a calculated response is an important mind shift that opens organizations up to processing all types and formats of data to produce new and valuable insights as a return on their data investment. These insights aren't typically exposed by using only mainstream, noncognitive approaches.
Another Watson plus is that while consuming data, Watson converts unstructured data into structured data, which then allows that data to be available for those traditional downstream, noncognitive, more mainstream analytical and reporting tools and solutions.
The techniques applied by IBM Watson allow the possibility of using not just the original questions but also subsequent questions to find the right answers, possibly inferred by assembling multiple fragments of raw data and artifacts from multiple sources via machine learning algorithms. Watson provides this expertise to everyone, with the goal of addressing an entirely new class of problems and solutions that will fundamentally change the relationship of people, business, and computers.
This is the objective of IBM Watson, and is most likely one of the objectives of you, the reader of this book.
With any luck, as you work through the following chapters and gain a level of comfort in using IBM Watson Analytics, you will begin to think about and approach problems and opportunities in a new way.
In the following sections of this chapter, we will review the fundamentals of the IBM Watson interface, as well as some of the basic tasks you'll need to be familiar with in order to successfully work through the case study examples given in the following chapters.
Let's go!
IBM Cloud prerequisites
IBM Watson lives in the cloud (the IBM Cloud). The cloud environment makes it relatively easy to get started as there are actually very few prerequisites that you need to access IBM Watson Analytics (and the IBM Cloud platform overall). In fact, all you really need to get yourself up and running is an up-to-date web browser (most will work quite adequately) and your willingness to discover and learn.
The following are the official browser minimum requirements (as of the time of writing):
Chrome
: Latest version for your operating system
Firefox
: Latest regular and ESR versions for your operating system
Internet Explorer
: Version 11
Edge
: Latest version for Windows
Safari
: Latest version for Mac
Exploring the Watson interface
With any new endeavor, one would be wise to take some time before actually bringing or attempting any project work (so, at the startup stage) in order to focus on becoming comfortable, or at least somewhat familiar, with the tool or technology's fundamentals.
In this chapter, as we look at IBM Watson, obtaining this understanding starts first with procuring access to IBM Watson Analytics and, as a next step, the IBM Cloud platform.
First, a little bit on the IBM Cloud. The IBM Cloud is a platform offering a rich assortment of infrastructure, cognitive, software, and services (and a lot of documentation and examples) with the aim of jump starting and otherwise accelerating the pace of business.
The IBM Cloud platform is where you can access the full power of the IBM Watson platform, where you can build new and exciting applications, using prebuilt services and APIs.
Once you obtain your access, you will have the opportunity to click through a number of welcome, how-to, and helpful hint tutorials. The introductory window is shown in the following screenshot:
The reader should take note that the official product documentation refers to the IBM Cloud user interface as the Cloud Console, where all of your cloud resources, as well as components (including IBM Watson), can be accessed and managed.
After you log in, your dashboard will contain many links to various resources and functionalities based upon your account type. The following screenshot shows the IBM Cloud main or start page (sometimes even called the welcome page), which is referred to as the IBM Cloud Dashboard:
We won't take the time here to go through these wonderful IBM Cloud platform tutorial videos (but you definitely should review as many of them as possible); instead, we will talk a bit about the basic components of the IBM Cloud Console and then quickly-jump into the IBM Watson Analytics interface.
The menu bar
The menu bar (located across the top of the dashboard) is sometimes referred to as the title bar. The following is a screenshot showing the IBM Cloud menu bar:
In the following sections, we will look at the icons and options in the menu bar, starting from the top left side.
Menu icon
The menu icon is the first image on the left of the menu bar (Hint: it looks like a stack of three lines). Clicking on this icon will display a vertical list of the available menu selections on the platform. The following screenshot shows the menu selection list:
IBM Cloud
As we move to the right along the title bar, the next option is the IBM Cloud menu selection. Clicking on this option will always return you—send you back—to the start or main page.
Catalog
The Catalog menu selection sends you to the Catalog IBM Cloud page (shown in the following screenshot), where you can (based upon a selected filter type) do things such as manage your cloud infrastructure and access other IBM Cloud platform features:
Docs
Clicking the Docs menu item takes you to the Docs or Documentation Entry page (shown in the following screenshot). Here is where you can perform actions such as Search documentation, Get started by deploying your first app, or follow a specific IBM Cloud help thread that you are interested in:
Support
Clicking on the Support menu item displays a drop-down selection list (shown in the following screenshot) with various options for obtaining the best type or level of support based upon your particular needs. The support options included are as follows:
What's New
Access to the (IBM Cloud)
Support Center
The ability to enter or
Add
(a)
Ticket
(a ticket is your request for information or support assistance)
View
Tickets
(that is, all of your current and prior tickets)
Status
, where you have the ability to investigate issues reported by the entire IBM Cloud user community:
Manage
Clicking on the Manage menu option displays the various areas in which you have the ability to manage your IBM Cloud's Account, Billing and Usage, and Security:
Profile – avatar
Clicking on the Profile menu option displays access to view, update, and upgrade options for your IBM Cloud account. In addition, this is where you can officially log out of the IBM Cloud environment:
Online glossary, let's chat, and feedback
Another great resource for someone who is new to the IBM Cloud is the online glossary of terms, referred to as the IBM Cloud Glossary, which can be found at:
https://console.bluemix.net/docs/overview/glossary/index.html#glossr
In addition, on most pages within the IBM Cloud environment, you will see the following icon:
This is the Let's Chat icon which, by clicking, connects you within a few hours to a question and answer dialog with one or more IBM Cloud Support Experts. It is not a real-time chat session, but it is pretty efficient. Don't be afraid to give it a try, they are very helpful.
IBM is committed to growing and evolving the IBM Cloud platform and is keen on hearing your opinion. One testimonial to this commitment is the presence of the FEEDBACK label, which is visible on most of the pages within the IBM Cloud. Clicking on FEEDBACK presents you with the option to easily provide both specific or (more) general comments and suggestions, or, if you are having a problem, from here you can also enter a support ticket.
What about Watson?
Back to our menu icon. If you scroll down, you can click on Watson, which will send you to the IBM Watson main page, shown as follows:
The format of this page is similar in format to the IBM Cloud console main page, as there are helpful Get Started panels (sometimes called tiles) offering options across the top part of the page. These are links to Starter Kits, and beneath these most popular kits (Build a chatbot,Extract insights, and Convert audio into text) are the links to View all Starter Kits and Browse all Watson services.
If you scroll further down the page, you will find access to Watson Studio, as well other useful links such as SDKs, The Watson Blog, GitHub, and so on.
Accessing the IBM Watson platform
