This is the code repository for IBM Watson Projects, published by Packt.
Eight exciting projects that put artificial intelligence into practice for optimal business performance
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.
This book covers the following exciting features:
- 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
If you feel this book is for you, get your copy today!
All of the code is organized into folders. For example, Chapter02.
Following is what you need for this book: 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.
With the following software and hardware list you can run all code files present in the book (Chapter 1-10).
| Chapter | Software required | OS required |
|---|---|---|
| All | IBM Watson | Windows, Mac OS X, and Linux (Any) |
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Hands-On Natural Language Processing with Python [Packt] [Amazon]
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Natural Language Processing with Python Cookbook [Packt] [Amazon]
James Miller
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.
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