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Incorporate intelligence to your data-driven business insights and high accuracy business solutions Key FeaturesExplore IBM Watson capabilities such as Natural Language Processing (NLP) and machine learningBuild projects to adopt IBM Watson across retail, banking, and healthcareLearn forecasting, anomaly detection, and pattern recognition with ML techniquesBook 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 learnBuild a smart dialog system with cognitive assistance solutionsDesign a text categorization model and perform sentiment analysis on social media datasetsDevelop a pattern recognition application and identify data irregularities smartlyAnalyze trip logs from a driving services company to determine profitProvide insights into an organization's supply chain data and processesCreate personalized recommendations for retail chains and outletsTest forecasting effectiveness for better sales prediction strategiesWho 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.
Utilize Python and IBM Watson to put real-life use cases into production. KEY FEATURES ● Use of popular Python packages for building Machine Learning solutions from scratch. ● Practice various IBM Watson Machine Learning tools for Computer Vision and Natural Language Processing applications. ● Expert-led best practices to put your Machine Learning solutions into the production environment. DESCRIPTION This book will take you through the journey of some amazing tools IBM Watson has to offer to leverage your machine learning concepts to solve some real-life use cases that are pertinent to the current industry. This book explores the various Machine Learning fundamental concepts and how to use the Python programming language to deal with real-world use cases. It explains how to take your code and deploy it into IBM Cloud leveraging IBM Watson Machine Learning. While doing so, the book also introduces you to several amazing IBM Watson tools such as Watson Assistant, Watson Discovery, and Watson Visual Recognition to ease out various machine learning tasks such as building a chatbot, creating a natural language processing pipeline, or an optical object detection application without a single line of code. It covers Watson Auto AI with which you can apply various machine learning algorithms and pick out the best for your dataset without a single line of code. Finally, you will be able to deploy all of these into IBM Cloud and configure your application to maintain the production-level runtime. After reading this book, you will find yourself confident to administer any machine learning use case and deploy it into production without any hassle. You will be able to take up a complete end-to-end machine learning project with complete responsibility and deliver the best standards the current industry has to offer. Towards the end of this book, you will be able to build an end-to-end production-level application and deploy it into Cloud. WHAT YOU WILL LEARN ● Review the basics of Machine Learning and learn implementation using Python. ● Learn deployment using IBM Watson Studio and Watson Machine Learning. ● Learn how to use Watson Auto AI to automate hyperparameter tuning. ● Learn Watson Assistant, Watson Visual Recognition, and Watson Discovery. ● Learn how to implement the various layers of an end-to-end AI application. ● Learn all the configurations needed for production deployment to Cloud. WHO THIS BOOK IS FOR This book is for all data professionals, ML enthusiasts, and software developers who are looking for real solutions to be developed. The reader is expected to have a prior knowledge of the web application architecture and basic Python fundamentals. TABLE OF CONTENTS 1. Introduction to Machine Learning 2. Deep Learning 3. Features and Metrics 4. Build Your Own Chatbot 5. First Complete Machine Learning Project 6. Perfecting Our Model 7. Visual Recognition 8. Watson Discovery 9. Deployment and Others 10. Deploying the Food Ordering Bot
The Building Cognitive Applications with IBM Watson Services series is a seven-volume collection that introduces IBM® WatsonTM cognitive computing services. The series includes an overview of specific IBM Watson® services with their associated architectures and simple code examples. Each volume describes how you can use and implement these services in your applications through practical use cases. The series includes the following volumes: Volume 1 Getting Started, SG24-8387 Volume 2 Conversation, SG24-8394 Volume 3 Visual Recognition, SG24-8393 Volume 4 Natural Language Classifier, SG24-8391 Volume 5 Language Translator, SG24-8392 Volume 6 Speech to Text and Text to Speech, SG24-8388 Volume 7 Natural Language Understanding, SG24-8398 Whether you are a beginner or an experienced developer, this collection provides the information you need to start your research on Watson services. If your goal is to become more familiar with Watson in relation to your current environment, or if you are evaluating cognitive computing, this collection can serve as a powerful learning tool. This IBM Redbooks® publication, Volume 1, introduces cognitive computing, its motivating factors, history, and basic concepts. This volume describes the industry landscape for cognitive computing and introduces Watson, the cognitive computing offering from IBM. It also describes the nature of the question-answering (QA) challenge that is represented by the Jeopardy! quiz game and it provides a high-level overview of the QA system architecture (DeepQA), developed for Watson to play the game. This volume charts the evolution of the Watson Developer Cloud, from the initial DeepQA implementation. This book also introduces the concept of domain adaptation and the processes that must be followed to adapt the various Watson services to specific domains.
The Building Cognitive Applications with IBM Watson Services series is a seven-volume collection that introduces IBM® Watson cognitive computing services. The series includes an overview of specific Watson services with their associated architectures and simple code examples. Each volume describes how you can use and implement these services in your applications through practical use cases. The series includes the following volumes: Volume 1 Getting Started, SG24-8387 Volume 2 Conversation, SG24-8394 Volume 3 Visual Recognition, SG24-8393 Volume 4 Natural Language Classifier, SG24-8391 Volume 5 Language Translator, SG24-8392 Volume 6 Speech to Text and Text to Speech, SG24-8388 Volume 7 Natural Language Understanding, SG24-8398 Whether you are a beginner or an experienced developer, this collection provides the information you need to start your research on Watson services. If your goal is to become more familiar with Watson in relation to your current environment, or if you are evaluating cognitive computing, this collection can serve as a powerful learning tool. This IBM Redbooks® publication, Volume 3, introduces the IBM Watson® Visual Recognition service. The Watson Visual Recognition service uses deep learning algorithms to analyze images for scenes, objects, faces, and other content. This book introduces concepts that you need to understand in order to use this Watson service and provides simple code examples to illustrate the use of the APIs. This book includes examples of applications that demonstrate how to use the Watson Visual Recognition service in practical use cases. You can develop and deploy the sample applications by following along in a step-by-step approach and using provided code snippets. Alternatively, you can download an existing Git project to more quickly deploy the application.
Understand, design, and create cognitive applications using Watson’s suite of APIs. Key FeaturesDevelop your skills and work with IBM Watson APIs to build efficient and powerful cognitive appsLearn how to build smart apps to carry out different sets of activities using real-world use casesGet well versed with the best practices of IBM Watson and implement them in your daily workBook Description Cognitive computing is rapidly infusing every aspect of our lives riding on three important fields: data science, machine learning (ML), and artificial intelligence (AI). It allows computing systems to learn and keep on improving as the amount of data in the system grows. This book introduces readers to a whole new paradigm of computing – a paradigm that is totally different from the conventional computing of the Information Age. You will learn the concepts of ML, deep learning (DL), neural networks, and AI through the set of APIs provided by IBM Watson. This book will help you build your own applications to understand, plan, and solve problems, and analyze them as per your needs. You will learn about various domains of cognitive computing, such as NLP, voice processing, computer vision, emotion analytics, and conversational systems, using different IBM Watson APIs. From this, the reader will learn what ML is, and what goes on in the background to make computers "do their magic," as well as where these concepts have been applied. Having achieved this, the readers will then be able to embark on their journey of learning, researching, and applying the concept in their respective fields. What you will learnGet well versed with the APIs provided by IBM Watson on IBM CloudLearn ML, AI, cognitive computing, and neural network principlesImplement smart applications in fields such as healthcare, entertainment, security, and moreUnderstand unstructured content using cognitive metadata with the help of Natural Language UnderstandingUse Watson’s APIs to create real-life applications to realize their capabilitiesDelve into various domains of cognitive computing, such as media analytics, embedded deep learning, computer vision, and moreWho this book is for This book is for beginners and novices; having some knowledge about artificial intelligence and deep learning is an advantage, but not a prerequisite to benefit from this book. We explain the concept of deep learning and artificial intelligence through the set of tools IBM Watson provides.
Inspiring innovation & culinary exploration. Outside the box. Creative. Whether in the fields of medicine, engineering or cooking, the ability to break the mold and imagine new concepts has long been considered a purely human ability. Until now. With Watson and the poer of cognitive computing, professionals and creators no longer need to rely on experience, intuition and elisive inspiration to make new discoveries. Chef Wtson is the result of purposeful innovation, a collaboration between the Institute of Culinary Education and IBM Watson, thty his produced a groundbreaking cookbook unlike any you've ever seen before.
The Building Cognitive Applications with IBM Watson Services series is a seven-volume collection that introduces IBM® WatsonTM cognitive computing services. The series includes an overview of specific IBM Watson® services with their associated architectures and simple code examples. Each volume describes how you can use and implement these services in your applications through practical use cases. The series includes the following volumes: Volume 1 Getting Started, SG24-8387 Volume 2 Conversation, SG24-8394 Volume 3 Visual Recognition, SG24-8393 Volume 4 Natural Language Classifier, SG24-8391 Volume 5 Language Translator, SG24-8392 Volume 6 Speech to Text and Text to Speech, SG24-8388 Volume 7 Natural Language Understanding, SG24-8398 Whether you are a beginner or an experienced developer, this collection provides the information you need to start your research on Watson services. If your goal is to become more familiar with Watson in relation to your current environment, or if you are evaluating cognitive computing, this collection can serve as a powerful learning tool. This IBM Redbooks® publication, Volume 2, describes how the Watson Conversation service can be used to create chatbots and user agents that understand natural-language input and communicate with your users simulating a real human conversation. It introduces the concepts that you need to understand in order to use the Watson Conversation service. It provides examples of applications that integrate the Watson Conversation service with other IBM Bluemix® services, such as the IBM IoT Platform, Text to Speech, Speech to Text, and Weather Company® Data, to implement practical use cases. You can develop and deploy the sample applications by following along in a step-by-step approach and using provided code snippets. Alternatively, you can download an existing Git project to more quickly deploy the application.
IBM® WatsonTM Content Analytics (Content Analytics) Version 3.0 (formerly known as IBM Content Analytics with Enterprise Search (ICAwES)) helps you to unlock the value of unstructured content to gain new actionable business insight and provides the enterprise search capability all in one product. Content Analytics comes with a set of tools and a robust user interface to empower you to better identify new revenue opportunities, improve customer satisfaction, detect problems early, and improve products, services, and offerings. To help you gain the most benefits from your unstructured content, this IBM Redbooks® publication provides in-depth information about the features and capabilities of Content Analytics, how the content analytics works, and how to perform effective and efficient content analytics on your content to discover actionable business insights. This book covers key concepts in content analytics, such as facets, frequency, deviation, correlation, trend, and sentimental analysis. It describes the content analytics miner, and guides you on performing content analytics using views, dictionary lookup, and customization. The book also covers using IBM Content Analytics Studio for domain-specific content analytics, integrating with IBM Content Classification to get categories and new metadata, and interfacing with IBM Cognos® Business Intelligence (BI) to add values in BI reporting and analysis, and customizing the content analytics miner with APIs. In addition, the book describes how to use the enterprise search capability for the discovery and retrieval of documents using various query and visual navigation techniques, and customization of crawling, parsing, indexing, and runtime search to improve search results. The target audience of this book is decision makers, business users, and IT architects and specialists who want to understand and analyze their enterprise content to improve and enhance their business operations. It is also intended as a technical how-to guide for use with the online IBM Knowledge Center for configuring and performing content analytics and enterprise search with Content Analytics.
The Building Cognitive Applications with IBM Watson Services series is a seven-volume collection that introduces IBM® WatsonTM cognitive computing services. The series includes an overview of specific IBM Watson® services with their associated architectures and simple code examples. Each volume describes how you can use and implement these services in your applications through practical use cases. The series includes the following volumes: Volume 1 Getting Started, SG24-8387 Volume 2 Conversation, SG24-8394 Volume 3 Visual Recognition, SG24-8393 Volume 4 Natural Language Classifier, SG24-8391 Volume 5 Language Translator, SG24-8392 Volume 6 Speech to Text and Text to Speech, SG24-8388 Volume 7 Natural Language Understanding, SG24-8398 Whether you are a beginner or an experienced developer, this collection provides the information you need to start your research on Watson services. If your goal is to become more familiar with Watson in relation to your current environment, or if you are evaluating cognitive computing, this collection can serve as a powerful learning tool. This IBM Redbooks® publication, Volume 6, introduces the Watson Text to Speech (converts written text into natural sounding audio in various languages and voices) and Watson Speech to Text (converts audio voice into written text) services. This book introduces concepts that you need to understand to use these Watson services and provides simple code examples to illustrate the use of the APIs. This book includes examples of applications that demonstrate how to use the Watson Text to Speech and Speech to Text services in practical use cases. You can develop and deploy the sample applications by following along in a step-by-step approach and using provided code snippets. Alternatively, you can download an existing Git project to more quickly deploy the application.
This book presents reports and methods that demonstrate the ease with which cognitive applications can be built using IBM Watson application program interfaces (APIs). It includes application reports from two IBM Watson API-based competitions – Hackathon (24 hours) and a Challenge task (~3 months). It also features a selection of papers presented at I-CARE 2016, the IBM Collaborative Academia Research Exchange event, from the areas of “Theory and Cognitive Computing”, “Data Platforms and Systems,” and “Societal Applications.” IBM has a long tradition of research collaboration with colleagues in academia, and I-CARE is an annual event initiated in 2009 to promote collaborative innovation and learning, and explore new ways of fostering a culture of innovation. I-CARE’s main goal is to “amalgamate” the thought leadership in Indian academia with that in industry, and foster a symbiotic environment for establishing a rich research culture in India. The 8th edition of I-CARE presents a collection of thought-provoking ideas and novel Indian research projects related to three crucial areas: cognitive computing, systems and platforms that support large-scale data processing and practical systems that are designed for the public good.