Instead, you'll find easy-to-digest instruction and two complete hands-on serverless AI builds in this must-have guide! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Author: Peter Elger
Publisher: Manning Publications
Companies everywhere are moving everyday business processes over to the cloud, and AI is increasingly being given the reins in these tasks. As this massive digital transformation continues, the combination of serverless computing and AI promises to become the de facto standard for business-to-consumer platform development—and developers who can design, develop, implement, and maintain these systems will be in high demand! AI as a Service is a practical handbook to building and implementing serverless AI applications, without bogging you down with a lot of theory. Instead, you'll find easy-to-digest instruction and two complete hands-on serverless AI builds in this must-have guide! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Text, video and speech analysis are among the powerful machine learning features that can be used. This book is the easiest way to get started with the Google Cloud AI services suite and open up the world of smarter applications.
Author: Arvind Ravulavaru
Publisher: Packt Publishing Ltd
Leverage the power of various Google Cloud AI Services by building a smart web application using MEAN Stack Key Features Start working with the Google Cloud Platform and the AI services it offers Build smart web applications by combining the power of Google Cloud AI services and the MEAN stack Build a web-based dashboard of smart applications that perform language processing, translation, and computer vision on the cloud Book Description Cognitive services are the new way of adding intelligence to applications and services. Now we can use Artificial Intelligence as a service that can be consumed by any application or other service, to add smartness and make the end result more practical and useful. Google Cloud AI enables you to consume Artificial Intelligence within your applications, from a REST API. Text, video and speech analysis are among the powerful machine learning features that can be used. This book is the easiest way to get started with the Google Cloud AI services suite and open up the world of smarter applications. This book will help you build a Smart Exchange, a forum application that will let you upload videos, images and perform text to speech conversions and translation services. You will use the power of Google Cloud AI Services to make our simple forum application smart by validating the images, videos, and text provided by users to Google Cloud AI Services and make sure the content which is uploaded follows the forum standards, without a human curator involvement. You will learn how to work with the Vision API, Video Intelligence API, Speech Recognition API, Cloud Language Process, and Cloud Translation API services to make your application smarter. By the end of this book, you will have a strong understanding of working with Google Cloud AI Services, and be well on the way to building smarter applications. What you will learn Understand Google Cloud Platform and its Cloud AI services Explore the Google ML Services Work with an Angular 5 MEAN stack application Integrate Vision API, Video Intelligence API for computer vision Be ready for conversational experiences with the Speech Recognition API, Cloud Language Process and Cloud Translation API services Build a smart web application that uses the power of Google Cloud AI services to make apps smarter Who this book is for This book is ideal for data professionals and web developers who want to use the power of Google Cloud AI services in their projects, without the going through the pain of mastering machine learning for images, videos and text. Some familiarity with the Google Cloud Platform will be helpful.
Through interviews with consumers and executives of AIaaS vendors, author Mike Barlow examines the primary driver of this new approach: AI is simply too big for any single device or system.
Author: Mike Barlow
Category: Artificial intelligence
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.
Author: Rob High
Publisher: Packt Publishing Ltd
Understand, design, and create cognitive applications using Watson’s suite of APIs. Key Features Develop your skills and work with IBM Watson APIs to build efficient and powerful cognitive apps Learn how to build smart apps to carry out different sets of activities using real-world use cases Get well versed with the best practices of IBM Watson and implement them in your daily work Book 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 learn Get well versed with the APIs provided by IBM Watson on IBM Cloud Learn ML, AI, cognitive computing, and neural network principles Implement smart applications in fields such as healthcare, entertainment, security, and more Understand unstructured content using cognitive metadata with the help of Natural Language Understanding Use Watson’s APIs to create real-life applications to realize their capabilities Delve into various domains of cognitive computing, such as media analytics, embedded deep learning, computer vision, and more Who 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.
In this book, you will learn about the basic concepts of Machine Learning and Natural Language Processing.
Author: Navin Sabharwal
Publisher: BPB Publications
A step-by-step guide to build machine learning and NLP models using Google AutoML KEY FEATURES •Understand the basic concepts of Machine Learning and Natural Language Processing •Understand the basic concepts of Google AutoML, AI Platform, and Tensorflow •Explore the Google AutoML Natural Language service •Understand how to implement NLP models like Issue Categorization Systems using AutoML •Understand how to release the features of AutoML models as REST APIs for other applications •Understand how to implement the NLP models using the Google AI Platform DESCRIPTION Google AutoML and AI Platform provide an innovative way to build an AI-based system with less effort. In this book, you will learn about the basic concepts of Machine Learning and Natural Language Processing. You will also learn about the Google AI services such as AutoML, AI Platform, and Tensorflow, Google’s deep learning library, along with some practical examples using these services in real-life scenarios. You will also learn how the AutoML Natural Language service and AI Platform can be used to build NLP and Machine Learning models and how their features can be released as REST APIs for other applications. In this book, you will also learn the usage of Google’s BigQuery, DataPrep, and DataProc for building an end-to-end machine learning pipeline. This book will give you an in-depth knowledge of Google AutoML and AI Platform by implementing real-life examples such as the Issue Categorization System, Sentiment Analysis, and Loan Default Prediction System. This book is relevant to the developers, cloud enthusiasts, and cloud architects at the beginner and intermediate levels. WHAT YOU WILL LEARN By the end of this book, you will learn how Google AutoML, AI Platform, BigQuery, DataPrep, and Dapaproc can be used to build an end-to-end machine learning pipeline. You will also learn how different types of AI problems can be solved using these Google AI services. A step-by-step implementation of some common NLP problems such as the Issue Categorization System and Sentiment Analysis System that provide you with hands-on experience in building complex AI-based systems by easily leveraging the GCP AI services. WHO IS THIS BOOK FOR This book is for machine learning engineers, NLP users, and data professionals who want to develop and streamline their ML models and put them into production using Google AI services. Prior knowledge of python programming and the basics of machine learning would be preferred. TABLE OF CONTENTS 1. Introduction to Artificial Intelligence 2. Introducing the Google Cloud Platform 3. AutoML Natural Language 4. Google AI Platform 5. Google Data Analysis, Preparation, and Processing Services AUTHOR BIO Navin Sabharwal: Navin is an innovator, leader, author, and consultant in AI and Machine Learning, Cloud Computing, Big Data Analytics, Software Product Development, Engineering, and R&D. He has authored books on technologies such as GCP, AWS, Azure, AI and Machine Learning systems, IBM Watson, chef, GKE, Containers, and Microservices. He is reachable at [email protected]
Amit Agrawal: Amit holds a master’s degree in Computer Science and Engineering from MNNIT (Motilal Nehru National Institute of Technology, Allahabad), one of the premier institutes of Engineering in India. He is working as a principal Data Scientist and researcher, delivering solutions in the fields of AI and Machine Learning. He is responsible for designing end-to-end solutions and architecture for enterprise products. He is reachable at [email protected]
STAFFING AN A.I. SERVICE the simultaneous introduction of This was largely
due to the promise reasonable standards of animal nutri of economic advantage
that the techtion , disease control and husbandry , nique had to offer . and of ...
Category: Animal industry
This paper will provide answers to the research question How do AI startups build trust in their smart service systems? by applying the theory of trust to smart service systems and AI startups.
Author: Lobosch Pannewitz
Publisher: GRIN Verlag
Category: Business & Economics
Bachelor Thesis from the year 2017 in the subject Business economics - Company formation, Business Plans, grade: 1,3, Free University of Berlin (Fachbereich Wirtschaftswissenschaft), course: Wirtschaftsinformatik, language: English, abstract: The global economy is shifting labor from agriculture and manufacturing to services. Globe-spanning service-based business models enabled by information technology (IT) and increas-ingly specialized businesses and professions have transformed our economies. Service innova-tion is key in order to achieve growth for this more-service-focused-than-ever world economy to thrive. Scholars recognize a need for new ways of value-creation that can propel economic growth and the development of more effective services (Vargo, Maglio, & Akaka, 2008). One answer to respond to that need is the re-organization of the production of services in so-called service systems. This approach is particularly useful for knowledge-intensive industries and noticeable for example in the artificial intelligence (AI) industry, a rapidly evolving, hy-per-innovative ecosystem with new players coming up at frequent intervals. AI startups offer their services through smart service systems or they try to make their customer’s and their own service systems smarter by adding AI services to the process of value co-creation. The industry heavily relies on software as a service (SaaS) business models which represent the ideal-typical shift to a service-dominant (S-D) logic thinking. When it comes to the acceptance of those new services, trust is a vital concern. While it has always been an important issue in services, trust in smart service systems becomes crucial. As AI startups’ service propositions are far from familiar to their potential clients, they have got to go the extra mile to build trust in their smart service systems. This paper will provide answers to the research question How do AI startups build trust in their smart service systems? by applying the theory of trust to smart service systems and AI startups. As website quality is an important trust-building lever the research question will be answered by exploring trust building measures in a sample of 26 AI startups’ websites. The major findings include that AI startups do not make their smart service systems as trans-parent as they could through their websites, that showcasing recognition by third parties oc-curs mostly through inexpensive tools that are easy to implement, and that all AI startups offer indirect channels to get in contact with them but less offer richer channels.
This book will help you design, develop, and manage robust, secure, and dynamic solutions to successfully meet your business needs.
Author: Victor Dantas
Publisher: Packt Publishing Ltd
Achieve your infrastructure goals and optimize business processes by designing robust, highly available, and dynamic solutions Key Features Gain hands-on experience in designing and managing high-performance cloud solutions Leverage Google Cloud Platform to optimize technical and business processes using cutting-edge technologies and services Use Google Cloud Big Data, AI, and ML services to design scalable and intelligent data solutions Book Description Google has been one of the top players in the public cloud domain thanks to its agility and performance capabilities. This book will help you design, develop, and manage robust, secure, and dynamic solutions to successfully meet your business needs. You'll learn how to plan and design network, compute, storage, and big data systems that incorporate security and compliance from the ground up. The chapters will cover simple to complex use cases for devising solutions to business problems, before focusing on how to leverage Google Cloud's Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS) capabilities for designing modern no-operations platforms. Throughout this book, you'll discover how to design for scalability, resiliency, and high availability. Later, you'll find out how to use Google Cloud to design modern applications using microservices architecture, automation, and Infrastructure-as-Code (IaC) practices. The concluding chapters then demonstrate how to apply machine learning and artificial intelligence (AI) to derive insights from your data. Finally, you will discover best practices for operating and monitoring your cloud solutions, as well as performing troubleshooting and quality assurance. By the end of this Google Cloud book, you'll be able to design robust enterprise-grade solutions using Google Cloud Platform. What you will learn Get to grips with compute, storage, networking, data analytics, and pricing Discover delivery models such as IaaS, PaaS, and SaaS Explore the underlying technologies and economics of cloud computing Design for scalability, business continuity, observability, and resiliency Secure Google Cloud solutions and ensure compliance Understand operational best practices and learn how to architect a monitoring solution Gain insights into modern application design with Google Cloud Leverage big data, machine learning, and AI with Google Cloud Who this book is for This book is for cloud architects who are responsible for designing and managing cloud solutions with GCP. You'll also find the book useful if you're a system engineer or enterprise architect looking to learn how to design solutions with Google Cloud. Moreover, cloud architects who already have experience with other cloud providers and are now beginning to work with Google Cloud will benefit from the book. Although an intermediate-level understanding of cloud computing and distributed apps is required, prior experience of working in the public and hybrid cloud domain is not mandatory.
While highlighting a broad range of topics including construction management, public transportation, and smart agriculture, this book is ideally designed for engineers, entrepreneurs, urban planners, architects, policymakers, researchers, ...
Author: Lyu, Kangjuan
Publisher: IGI Global
Cities are the next frontier for artificial intelligence to permeate. As smart urban environments become possible, probable, and even preferred, artificial intelligence offers the chance for even further advancement through infrastructure and industry boosting. Opportunity overflows, but without thorough research to guide a complicated development and implementation process, urban environments can become disorganized and outright dangerous for citizens. AI-Based Services for Smart Cities and Urban Infrastructure is a collection of innovative research that explores artificial intelligence (AI) applications in urban planning. In addition, the book looks at how the internet of things and AI can work together to enable a real smart city and discusses state-of-the-art techniques in urban infrastructure design, construction, operation, maintenance, and management. While highlighting a broad range of topics including construction management, public transportation, and smart agriculture, this book is ideally designed for engineers, entrepreneurs, urban planners, architects, policymakers, researchers, academicians, and students.
But the key word in Teknowledge's success is service . Not product . Tek is trying
to get away from relying SO heavily on the service aspects of expert systems :
consulting , training , education , custom development . It wants to have a greater
Category: Artificial intelligence
This book explains how you can enrich the data you have loaded into Power BI Desktop by accessing a suite of Artificial Intelligence (AI) features.
Author: Markus Ehrenmueller-Jensen
This book explains how you can enrich the data you have loaded into Power BI Desktop by accessing a suite of Artificial Intelligence (AI) features. These AI features are built into Power BI Desktop and help you to gain new insights from existing data. Some of the features are automated and are available to you at the click of a button or through writing Data Analysis Expressions (DAX). Other features are available through writing code in either the R, Python, or M languages. This book opens up the entire suite of AI features to you with clear examples showing when they are best applied and how to invoke them on your own datasets. No matter if you are a business user, analyst, or data scientist – Power BI has AI capabilities tailored to you. This book helps you learn what types of insights Power BI is capable of delivering automatically. You will learn how to integrate and leverage the use of the R and Python languages for statistics, how to integrate with Cognitive Services and Azure Machine Learning Services when loading data, how to explore your data by asking questions in plain English ... and more! There are AI features for discovering your data, characterizing unexplored datasets, and building what-if scenarios. There’s much to like and learn from this book whether you are a newcomer to Power BI or a seasoned user. Power BI Desktop is a freely available tool for visualization and analysis. This book helps you to get the most from that tool by exploiting some of its latest and most advanced features. What You Will Learn Ask questions in natural language and get answers from your data Let Power BI explain why a certain data point differs from the rest Have Power BI show key influencers over categories of data Access artificial intelligence features available in the Azure cloud Walk the same drill down path in different parts of your hierarchy Load visualizations to add smartness to your reports Simulate changes in data and immediately see the consequences Know your data, even before you build your first report Create new columns by giving examples of the data that you need Transform and visualize your data with the help of R and Python scripts Who This Book Is For For the enthusiastic Power BI user who wants to apply state-of-the-art artificial intelligence (AI) features to gain new insights from existing data. For end-users and IT professionals who are not shy of jumping into a new world of machine learning and are ready to make that step and take a deeper look into their data. For those wanting to step up their game from doing simple reporting and visualizations by making the move into diagnostic and predictive analysis.
TABLE 1 : A.I. EXPERIENCE A.I. Prior Years A.I. in 1981 Yes ( % ) No ( % ) Yes
89.5 10.4 No 39.7 60.3 Total 71.3 28.7 to natural In one series of questions , the
respondents were asked to compare A.I. service . The overall response is shown
This book covers the latest easy-to-use APIs and services from Microsoft, including Azure IoT, Cognitive Services APIs, Blockchain as a Service (BaaS), and Machine Learning Studio.
Author: Nishith Pathak
Create applications using Industry 4.0. Discover how artificial intelligence (AI) and machine learning (ML) capabilities can be enhanced using the Internet of things (IoT) and secured using Blockchain, so your latest app can be not just smarter but also more connected and more secure than ever before. This book covers the latest easy-to-use APIs and services from Microsoft, including Azure IoT, Cognitive Services APIs, Blockchain as a Service (BaaS), and Machine Learning Studio. As you work through the book, you’ll get hands-on experience building an example solution that uses all of these technologies—an IoT suite for a smart healthcare facility. Hosted on Azure and networked using Azure IoT, the solution includes centralized patient monitoring, using Cognitive Services APIs for face detection, recognition, and tracking. Blockchain is used to create trust-based security and inventory management. Machine learning is used to create predictive solutions to proactively improve quality of life. By the end of the book, you’ll be confident creating richer and smarter applications using these technologies. What You’ll Learn Know the technologies underpinning Industry 4.0 and AI 2.0 Develop real-time solutions using IoT in Azure Bring the smart capabilities of AI 2.0 into your application using a simple API call Host and manage your solution on Azure Understand Blockchain as a Service Capture and analyze data on the fly Make predictions using existing data Who This Book Is For Novice and intermediate .NET developers and architects who want to learn what it takes to create a modern or next-generation application
The BCS has an excellent AI interest group that puts out a monthly newsletter
edited by Park S. Gerald. ... BYTE Listings, a service of the magazine, allows you
to purchase the source code from a single issue on an annual issue basis.
Category: Artificial intelligence
Otherwise, the server is busy, and job As must wait until the previous job Ai-1
completes service and departs from the system at time d;–1. Unfortunately,
determination of the output sequence (Di, di), i > 1, is decidedly nontrivial for an
Author: John A. Miller
Publisher: Society for Computer Simulation International
Category: Digital computer simulation
Each province in this country has a Provincial Animal Health Service . It has
already been stated that all A.I. bulls must be previously examined by the
veterinary surgeons attached to these Services . In addition to this , the task of the
Author: Netherlands. Veeartsenijkundig Staatstoezicht
Category: Veterinary medicine
DELEGATES and guests attending the November 9 & 10 , 1973 Eastern AI
Annual Delegates meeting at Syracuse went ... 2 - Cooperative application with
cooperative associations emerging as service businesses engaged in AI as
service to ...
Category: Artificial insemination
Outputs are products, services, and accompanying information flowing from an
activity. In seeking continuous business improvement, an overall examination of
variations in performances of key organizational activities and their causes is ...
Author: Burton S. Kaliski
Publisher: MacMillan Reference Library
Contains over 315 alphabetically arranged articles that provide information about the major functional areas of business, covering accounting, economics, finance, information systems, law, management, and marketing, as well as organizations in business and government, and federal legislation.
In this role he traveled to nearly all the major AI laboratories in the United States
and became acquainted with all the ... He did, however, unnerve a particularly
skilled tennis opponent once with his call on a service ace, "Too fast, Dave, take ...
Category: Artificial intelligence
A.I. Service Tests Recording Device Death of Proven Sire In accordance with the
N.S.W. Milk Board's A.I. Service policy of improving when and where possible its
service to farmers , a trial has been commenced with the use of a machine for ...
Author: New South Wales. Milk Board