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

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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.

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.

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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.

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.

, 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.

, 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.