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IBM Watson Projects
IBM Watson Projects

IBM Watson Projects: Eight exciting projects that put artificial intelligence into practice for optimal business performance

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Profile Icon Armen Pischdotchian Profile Icon James D. Miller
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Arrow left icon
Profile Icon Armen Pischdotchian Profile Icon James D. Miller
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Paperback Sep 2018 340 pages 1st Edition
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IBM Watson Projects

A Basic Watson Project

In this chapter, we have elected to use a use case project that will analyze trip log data from a driving service company to determine which trip characteristics may have a direct effect on a trip's profitability, considering what type of trip is most profitable and which are prone to complications. This first Watson project serves to cover the basics of a simple Watson project—preparing the reader for upcoming, more complex projects presented in the following chapters.

We'll break down this first chapter into:

  • The problem defined
  • Getting started
  • Building your Watson project
  • Reviewing the results

The problem defined

As we said, we'll keep this first project example quite simple by focusing more on concepts and fundamentals, rather than spending time defining and exploring every detail (that will come in subsequent chapters!).

Let's start with some background. Suppose there is a group providing state-wide transportation services. This group originally began with a single driver, a car, and a van. Over time, the owner sold out to a group of investors who have evolved the company, now employing a large team of professional drivers and offering a full range of (driving) services for individuals and specific events, with vehicles chosen from an inventory of specialized vehicles. The owners are enjoying a steady business but not, unfortunately, steady profits. What can be done?

From the beginning, drivers had to log all information about each trip and submit that...

Getting started

Recently, Stephen Archut, who has held the position of Product Marketing Manager, IBM Watson Analytics, indicated that the key capabilities of Watson Analytics include:

  • Automated data discovery
  • Exploration
  • Guided predictive analytics
  • Recommended visualizations
  • Dashboard creation
  • Visual storytelling

Further, he has said that these are all activities that business users perform on a daily basis and that Watson Analytics can accelerate. He also explained that Watson solutions aim to enhance, scale, and accelerate human expertise, targeting a wide range of complex challenges in the world today. Watson Analytics itself will understand, perceive, and relate information at a human level for your business problems, combining analytical insights with your expertise and experience to improve everyday decisions.

With these remarks in mind, we can get started with our project...

Building your Watson project

In this section we will go through a first project covering the basics of a simple Watson Analytics project, preparing you for upcoming, more complex projects presented in later chapters.

Loading your data

To actually start using Watson Analytics, go through the following steps:

  1. You'll need to log in and, from the main or Welcome page, click on the +Add icon as shown in the following screenshot:
  1. From there, you will see Create something new and add your data. Of course, we want to add our trip data, so we can choose between two methods: Drop file or browse or Upload data. Typically, for more realistically sized data files, you'll want to select Upload data and then browse to the file...

Refine or Explore

We should take note here that we jumped right into refining our data. Sometimes, especially if you are dealing with data completely new to you, you may spend time first exploring your data using the Watson Analytics Explore feature. We will spend time creating explorations later in this book, but for now it is good to mention, that if you refine a dataset, the changes that you make to it are available throughout Watson in Predict, Explore, and Assemble, but if you modify the data in an exploration, the changed data is available only in that exploration.

Creating a prediction

The objective of Watson Analytics is to give you the ability to create highly interpretable insights from your data based on complex modeling—without having to possess a deep understanding of each and every modeling algorithm.

Using Watson Predict, Watson Analytics uses these sophisticated algorithms to quickly and efficiently deliver predictions based on your data.

The predictions include visualizations and text descriptions of the analyses that Watson Analytics runs. You can use the visualizations to see analyses at a glance and read the text for supporting explanations and statistical details.

Because Watson Analytics automatically picks the right statistical tests for the data, you don't have to be know which test is best or which one to run.

  1. To begin, go to the Watson Analytics Welcome page, and click on Predict:
  1. Watson will then display...

Summary

In this chapter, we used a simple use case to cover the fundamental steps that are part of almost any Watson Analytics project. We started by stating an objective for the project by defining a realistic use case problem to solve, then gathered the data, loaded it into Watson Analytics (as an Excel Worksheet), and used Watson to refine the data before finally creating a prediction and reviewing the results.

At this point, the reader should have a clear understanding of how to create a Watson Analytics project.

In the next chapter, we will focus on analyzing how effective a supply chain is for a retail department store, using Watson Analytics in an attempt to isolate the causes of delivery performance.

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Key benefits

  • •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

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.

Who is this book 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 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
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Table of Contents

11 Chapters
The Essentials of IBM Watson Chevron down icon Chevron up icon
A Basic Watson Project Chevron down icon Chevron up icon
An Automated Supply Chain Scenario Chevron down icon Chevron up icon
Healthcare Dialoguing Chevron down icon Chevron up icon
Social Media Sentiment Analysis Chevron down icon Chevron up icon
Pattern Recognition and Classification Chevron down icon Chevron up icon
Retail and Personalized Recommendations Chevron down icon Chevron up icon
Integration for Sales Forecasting Chevron down icon Chevron up icon
Anomaly Detection in Banking Using AI Chevron down icon Chevron up icon
What's Next Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

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Federico Cussigh Oct 07, 2018
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An expert book writer should know that if the title of a technical book speaks about a platform, what the reader should find in it is the presentation of the whole platform.This book has a misleading title: it’s not about the whole IBM Watson platform offering, but it’s focused only on one technology: IBM Watson Analytics. On the top of this, in the preview and in the abstract of the book it was not possible to understand that! Last but not least, IBM Watson Analytics is no longer available for purchase: it has been cancelled from the IBM offering. I want my money back.
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