IBM Watson Projects
James Miller更新时间：2021-07-16 17:31:59
最新章节：Leave a review - let other readers know what you think封面
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
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Leave a review - let other readers know what you think
更新时间：2021-07-16 17:31:59