Download or read book Hands On Machine Learning on Google Cloud Platform written by Giuseppe Ciaburro and published by Packt Publishing Ltd. This book was released on 2018-04-30 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unleash Google's Cloud Platform to build, train and optimize machine learning models Key Features Get well versed in GCP pre-existing services to build your own smart models A comprehensive guide covering aspects from data processing, analyzing to building and training ML models A practical approach to produce your trained ML models and port them to your mobile for easy access Book Description Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions. This book is focused on making the most of the Google Machine Learning Platform for large datasets and complex problems. You will learn from scratch how to create powerful machine learning based applications for a wide variety of problems by leveraging different data services from the Google Cloud Platform. Applications include NLP, Speech to text, Reinforcement learning, Time series, recommender systems, image classification, video content inference and many other. We will implement a wide variety of deep learning use cases and also make extensive use of data related services comprising the Google Cloud Platform ecosystem such as Firebase, Storage APIs, Datalab and so forth. This will enable you to integrate Machine Learning and data processing features into your web and mobile applications. By the end of this book, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems. What you will learn Use Google Cloud Platform to build data-based applications for dashboards, web, and mobile Create, train and optimize deep learning models for various data science problems on big data Learn how to leverage BigQuery to explore big datasets Use Google’s pre-trained TensorFlow models for NLP, image, video and much more Create models and architectures for Time series, Reinforcement Learning, and generative models Create, evaluate, and optimize TensorFlow and Keras models for a wide range of applications Who this book is for This book is for data scientists, machine learning developers and AI developers who want to learn Google Cloud Platform services to build machine learning applications. Since the interaction with the Google ML platform is mostly done via the command line, the reader is supposed to have some familiarity with the bash shell and Python scripting. Some understanding of machine learning and data science concepts will be handy

Download or read book Practical AI on the Google Cloud Platform written by Micheal Lanham and published by O'Reilly Media. This book was released on 2020-10-20 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Working with AI is complicated and expensive for many developers. That's why cloud providers have stepped in to make it easier, offering free (or affordable) state-of-the-art models and training tools to get you started. With this book, you'll learn how to use Google's AI-powered cloud services to do everything from creating a chatbot to analyzing text, images, and video. Author Micheal Lanham demonstrates methods for building and training models step-by-step and shows you how to expand your models to accomplish increasingly complex tasks. If you have a good grasp of math and the Python language, you'll quickly get up to speed with Google Cloud Platform, whether you want to build an AI assistant or a simple business AI application. Learn key concepts for data science, machine learning, and deep learning Explore tools like Video AI and AutoML Tables Build a simple language processor using deep learning systems Perform image recognition using CNNs, transfer learning, and GANs Use Google's Dialogflow to create chatbots and conversational AI Analyze video with automatic video indexing, face detection, and TensorFlow Hub Build a complete working AI agent application

Download or read book Hands On Artificial Intelligence on Google Cloud Platform written by Anand Deshpande and published by . This book was released on 2020-03-06 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Practical AI on the Google Cloud Platform written by Micheal Lanham and published by . This book was released on 2020-12-08 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI is complicated, but cloud providers have stepped in to make it easier, offering free (or affordable) state-of-the-art models and training tools to get you started. In this book, AI novices will learn how to use Google's AI-powered cloud services to do everything from analyzing text, images, and video to creating a chatbot. Author Micheal Lanham takes you step-by-step through building models, training them, and then expanding on them to accomplish increasingly complex tasks. If you have a good grasp of math and the Python language, this book will get you up and running with Google Cloud Platform, whether you're looking to build a simple business AI application or an AI assistant. Learn key concepts for data science, machine learning, and deep learning Explore tools like Video AI, AutoML Tables, the Cloud Inference API, the Recommendations AI API, and BigQuery ML Perform image recognition using CNNs, transfer learning, and GANs Build a simple language processor using embeddings, RNNs, and Bidirectional Encoder Representations from Transformers (BERT) Use Dialogflow to build a chatbot Analyze video with automatic video indexing, face detection, and TF Hub

Download or read book The Definitive Guide to Google Vertex AI written by Jasmeet Bhatia and published by Packt Publishing Ltd. This book was released on 2023-12-29 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Implement machine learning pipelines with Google Cloud Vertex AI Key Features Understand the role of an AI platform and MLOps practices in machine learning projects Get acquainted with Google Vertex AI tools and offerings that help accelerate the creation of end-to-end ML solutions Implement Vision, NLP, and recommendation-based real-world ML models on Google Cloud Platform Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWhile AI has become an integral part of every organization today, the development of large-scale ML solutions and management of complex ML workflows in production continue to pose challenges for many. Google’s unified data and AI platform, Vertex AI, directly addresses these challenges with its array of MLOPs tools designed for overall workflow management. This book is a comprehensive guide that lets you explore Google Vertex AI’s easy-to-advanced level features for end-to-end ML solution development. Throughout this book, you’ll discover how Vertex AI empowers you by providing essential tools for critical tasks, including data management, model building, large-scale experimentations, metadata logging, model deployments, and monitoring. You’ll learn how to harness the full potential of Vertex AI for developing and deploying no-code, low-code, or fully customized ML solutions. This book takes a hands-on approach to developing u deploying some real-world ML solutions on Google Cloud, leveraging key technologies such as Vision, NLP, generative AI, and recommendation systems. Additionally, this book covers pre-built and turnkey solution offerings as well as guidance on seamlessly integrating them into your ML workflows. By the end of this book, you’ll have the confidence to develop and deploy large-scale production-grade ML solutions using the MLOps tooling and best practices from Google.What you will learn Understand the ML lifecycle, challenges, and importance of MLOps Get started with ML model development quickly using Google Vertex AI Manage datasets, artifacts, and experiments Develop no-code, low-code, and custom AI solution on Google Cloud Implement advanced model optimization techniques and tooling Understand pre-built and turnkey AI solution offerings from Google Build and deploy custom ML models for real-world applications Explore the latest generative AI tools within Vertex AI Who this book is for If you are a machine learning practitioner who wants to learn end-to-end ML solution development on Google Cloud Platform using MLOps best practices and tools offered by Google Vertex AI, this is the book for you.

Download or read book Data Analytics with Google Cloud Platform written by Murari Ramuka and published by BPB Publications. This book was released on 2019-12-16 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Step-by-step guide to different data movement and processing techniques, using Google Cloud Platform Services DESCRIPTION Modern businesses are awash with data, making data-driven decision-making tasks increasingly complex. As a result, relevant technical expertise and analytical skills are required to do such tasks. This book aims to equip you with enough knowledge of Cloud Computing in conjunction with Google Cloud Data platform to succeed in the role of a Cloud data expert. The current market is trending towards the latest cloud technologies, which is the need of the hour. Google being the pioneer, is dominating this space with the right set of cloud services being offered as part of GCP (Google Cloud Platform). At this juncture, this book will be very vital and will cover all the services that are being offered by GCP, putting emphasis on Data services. This book starts with sophisticated knowledge on Cloud Computing. It also explains different types of data services/technology and machine learning algorithm/Pre-Trained API through real-business problems, which are built on the Google Cloud Platform (GCP). With some of the latest business examples and hands-on guide, this book will enable the developers entering the data analytics fields to implement an end-to-end data pipeline, using GCP Data services. Through the course of the book, you will come across multiple industry-wise use cases, like Building Datawarehouse using Big Query, a sample real-time data analytics solution on machine learning and Artificial Intelligence that helped with the business decision, by employing a variety of data science approaches on Google Cloud environment. Whether yourÊbusinessÊis at the early stage of cloud implementation in its journey or well on its way to digital transformation,ÊGoogle Cloud'sÊsolutions and technologies will always help chart a path to success. This book can be used to develop the GCP concepts in an easy way. It contains many examples showcasing the implementation of a GCP service. It enables the learning of the basic and advance concepts of Google Cloud Data Platform. This book is divided into 7 chapters and provides a detailed description of the core concepts of each of the Data services offered by Google Cloud. KEY FEATURES Learn the basic concept of Cloud Computing along with different Cloud service provides with their supported Models (IaaS/PaaS/SaaS) Learn the basics of Compute Engine, App Engine, Container Engine, Project and Billing setup in the Google Cloud Platform Learn how and when to use Cloud DataFlow, Cloud DataProc and Cloud DataPrepÊ Build real-time data pipeline to support real-time analytics using Pub/Sub messaging service Setting up a fully managed GCP Big Data Cluster using Cloud DataProc for runningÊApache SparkÊandÊApache HadoopÊclusters in a simpler, more cost-efficient manner Learn how to use Cloud Data Studio for visualizing the data on top of Big Query Implement and understand real-world business scenarios for Machine Learning, Data Pipeline Engineering WHAT WILL YOU LEARN By the end of the book, you will have come across different data services and platforms offered by Google Cloud, and how those services/features can be enabled to serve business needs. You will also see a few case studies to put your knowledge to practice and solve business problems such as building a real-time streaming pipeline engine, Scalable Data Warehouse on Cloud, fully managed Hadoop cluster on Cloud and enabling TensorFlow/Machine Learning APIÕs to support real-life business problems. Remember to practice additional examples to master these techniques. WHO IS THIS BOOK FOR This book is for professionals as well as graduates who want to build a career in Google Cloud data analytics technologies. While no prior knowledge of Cloud Computing or related technologies is assumed, it will be helpful to have some data background and experience. One stop shop for those who wish to get an initial to advance understanding of the GCP data platform. The target audience will be data engineers/professionals who are new, as well as those who are acquainted with the tools and techniques related to cloud and data space.ÊÊ _Ê Ê Ê Individuals who have basic data understanding (i.e. Data and cloud) and have done some work in the field ofÊ data analytics, can refer/use this book to master their knowledge/understanding. _Ê Ê Ê The highlight of this book is that it will start with theÊ basic cloud computing fundamentals and will move on to cover the advance concepts on GCP cloud data analytics and hence can be referred across multiple different levels of audiences.Ê Table of Contents 1. GCP Overview and Architecture 2. Data Storage in GCPÊ 3. Data Processing in GCP with Pub/Sub and DataflowÊ 4. Data Processing in GCP with DataPrep and Dataflow 5. Big Query and Data Studio 6. Machine Learning with GCP 7. Sample Use cases and Examples

Download or read book Up and Running Google AutoML and AI Platform Building Machine Learning and NLP Models Using AutoML and AI Platform for Production Environment English Edition written by Navin Sabharwal and published by BPB Publications. This book was released on 2021-01-05 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: A step-by-step guide to build machine learning and NLP models using Google AutoML KEY FEATURESÊ ¥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 DESCRIPTIONÊÊ 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, GoogleÕs 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 GoogleÕs BigQuery, DataPrep, and DataProc for building an end-to-end machine learning pipeline. Ê 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 LEARNÊ 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. Ê WHO IS THIS BOOK FORÊ 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 BIOÊ 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 masterÕs 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].

Download or read book Architecting Google Cloud Solutions written by Victor Dantas and published by Packt Publishing Ltd. This book was released on 2021-05-14 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Achieve your business goals and build highly available, scalable, and secure cloud infrastructure by designing robust and cost-effective solutions as a Google Cloud Architect. Key FeaturesGain hands-on experience in designing and managing high-performance cloud solutionsLeverage Google Cloud Platform to optimize technical and business processes using cutting-edge technologies and servicesUse Google Cloud Big Data, AI, and ML services to design scalable and intelligent data solutionsBook 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 learnGet to grips with compute, storage, networking, data analytics, and pricingDiscover delivery models such as IaaS, PaaS, and SaaSExplore the underlying technologies and economics of cloud computingDesign for scalability, business continuity, observability, and resiliencySecure Google Cloud solutions and ensure complianceUnderstand operational best practices and learn how to architect a monitoring solutionGain insights into modern application design with Google CloudLeverage big data, machine learning, and AI with Google CloudWho 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.

Download or read book Visualizing Google Cloud written by Priyanka Vergadia and published by John Wiley & Sons. This book was released on 2022-03-11 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: Easy-to-follow visual walkthrough of every important part of the Google Cloud Platform The Google Cloud Platform incorporates dozens of specialized services that enable organizations to offload technological needs onto the cloud. From routine IT operations like storage to sophisticated new capabilities including artificial intelligence and machine learning, the Google Cloud Platform offers enterprises the opportunity to scale and grow efficiently. In Visualizing Google Cloud: Illustrated References for Cloud Engineers & Architects, Google Cloud expert Priyanka Vergadia delivers a fully illustrated, visual guide to matching the best Google Cloud Platform services to your own unique use cases. After a brief introduction to the major categories of cloud services offered by Google, the author offers approximately 100 solutions divided into eight categories of services included in Google Cloud Platform: Compute Storage Databases Data Analytics Data Science, Machine Learning and Artificial Intelligence Application Development and Modernization with Containers Networking Security You’ll find richly illustrated flowcharts and decision diagrams with straightforward explanations in each category, making it easy to adopt and adapt Google’s cloud services to your use cases. With coverage of the major categories of cloud models—including infrastructure-, containers-, platforms-, functions-, and serverless—and discussions of storage types, databases and Machine Learning choices, Visualizing Google Cloud: Illustrated References for Cloud Engineers & Architects is perfect for every Google Cloud enthusiast, of course. It is for anyone who is planning a cloud migration or new cloud deployment. It is for anyone preparing for cloud certification, and for anyone looking to make the most of Google Cloud. It is for cloud solutions architects, IT decision-makers, and cloud data and ML engineers. In short, this book is for YOU.

Download or read book Google Cloud AI Services Quick Start Guide written by Arvind Ravulavaru and published by Packt Publishing Ltd. This book was released on 2018-05-30 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Hands On Machine Learning on Google Cloud Platform written by Giuseppe Ciaburro and published by Packt Publishing Ltd. This book was released on 2018-04-30 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unleash Google's Cloud Platform to build, train and optimize machine learning models Key Features Get well versed in GCP pre-existing services to build your own smart models A comprehensive guide covering aspects from data processing, analyzing to building and training ML models A practical approach to produce your trained ML models and port them to your mobile for easy access Book Description Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions. This book is focused on making the most of the Google Machine Learning Platform for large datasets and complex problems. You will learn from scratch how to create powerful machine learning based applications for a wide variety of problems by leveraging different data services from the Google Cloud Platform. Applications include NLP, Speech to text, Reinforcement learning, Time series, recommender systems, image classification, video content inference and many other. We will implement a wide variety of deep learning use cases and also make extensive use of data related services comprising the Google Cloud Platform ecosystem such as Firebase, Storage APIs, Datalab and so forth. This will enable you to integrate Machine Learning and data processing features into your web and mobile applications. By the end of this book, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems. What you will learn Use Google Cloud Platform to build data-based applications for dashboards, web, and mobile Create, train and optimize deep learning models for various data science problems on big data Learn how to leverage BigQuery to explore big datasets Use Google’s pre-trained TensorFlow models for NLP, image, video and much more Create models and architectures for Time series, Reinforcement Learning, and generative models Create, evaluate, and optimize TensorFlow and Keras models for a wide range of applications Who this book is for This book is for data scientists, machine learning developers and AI developers who want to learn Google Cloud Platform services to build machine learning applications. Since the interaction with the Google ML platform is mostly done via the command line, the reader is supposed to have some familiarity with the bash shell and Python scripting. Some understanding of machine learning and data science concepts will be handy

Download or read book Google Certification Guide Google Professional Machine Learning Engineer written by Cybellium Ltd and published by Cybellium Ltd. This book was released on with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: Google Certification Guide - Google Professional Machine Learning Engineer Unlock the World of Machine Learning on Google Cloud Embark on a transformative journey to become a Google Professional Machine Learning Engineer with this comprehensive guide. Designed for those who aspire to master the application of machine learning techniques and tools in the Google Cloud environment, this book is an essential resource for professionals seeking to harness the power of ML in their projects and workflows. What Awaits Inside: Advanced ML Concepts and Practices: Dive deep into the world of machine learning on Google Cloud, covering services like AI Platform, TensorFlow, and BigQuery ML. Real-World Applications: Learn through practical scenarios and hands-on examples, illustrating the effective implementation of machine learning models and solutions on Google Cloud. Strategic Exam Preparation: Gain crucial insights into the certification exam's structure and content, complemented by comprehensive practice questions and preparation strategies. Cutting-Edge ML Trends: Stay updated with the latest advancements in Google Cloud machine learning technologies, ensuring your skills remain relevant and innovative. Authored by a Machine Learning Expert Written by an experienced practitioner in the field of machine learning on Google Cloud, this guide bridges the gap between theoretical knowledge and practical application, offering a rich and comprehensive learning experience. Your Comprehensive Guide to ML Certification Whether you’re an experienced machine learning engineer or looking to elevate your expertise in Google Cloud's ML offerings, this book is a valuable companion, guiding you through the intricacies of machine learning in Google Cloud and preparing you for the Professional Machine Learning Engineer certification. Elevate Your Machine Learning Journey This guide is more than a pathway to certification; it's a deep dive into the practical and innovative aspects of machine learning in the Google Cloud environment, designed to equip you with the skills and knowledge for a thriving career in this dynamic field. Begin Your Machine Learning Adventure Start your journey to becoming a certified Google Professional Machine Learning Engineer. This guide is not just about passing an exam; it's about unlocking new opportunities and frontiers in the exciting world of machine learning on Google Cloud. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com

Download or read book Hands On Artificial Intelligence for Beginners written by Patrick D. Smith and published by Packt Publishing Ltd. This book was released on 2018-10-31 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Grasp the fundamentals of Artificial Intelligence and build your own intelligent systems with ease Key FeaturesEnter the world of AI with the help of solid concepts and real-world use casesExplore AI components to build real-world automated intelligenceBecome well versed with machine learning and deep learning conceptsBook Description Virtual Assistants, such as Alexa and Siri, process our requests, Google's cars have started to read addresses, and Amazon's prices and Netflix's recommended videos are decided by AI. Artificial Intelligence is one of the most exciting technologies and is becoming increasingly significant in the modern world. Hands-On Artificial Intelligence for Beginners will teach you what Artificial Intelligence is and how to design and build intelligent applications. This book will teach you to harness packages such as TensorFlow in order to create powerful AI systems. You will begin with reviewing the recent changes in AI and learning how artificial neural networks (ANNs) have enabled more intelligent AI. You'll explore feedforward, recurrent, convolutional, and generative neural networks (FFNNs, RNNs, CNNs, and GNNs), as well as reinforcement learning methods. In the concluding chapters, you'll learn how to implement these methods for a variety of tasks, such as generating text for chatbots, and playing board and video games. By the end of this book, you will be able to understand exactly what you need to consider when optimizing ANNs and how to deploy and maintain AI applications. What you will learnUse TensorFlow packages to create AI systemsBuild feedforward, convolutional, and recurrent neural networksImplement generative models for text generationBuild reinforcement learning algorithms to play gamesAssemble RNNs, CNNs, and decoders to create an intelligent assistantUtilize RNNs to predict stock market behaviorCreate and scale training pipelines and deployment architectures for AI systemsWho this book is for This book is designed for beginners in AI, aspiring AI developers, as well as machine learning enthusiasts with an interest in leveraging various algorithms to build powerful AI applications.

Download or read book Google Cloud Platform in Action written by John J. (JJ) Geewax and published by Simon and Schuster. This book was released on 2018-08-15 with total page 920 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Google Cloud Platform in Action teaches you to build and launch applications that scale, leveraging the many services on GCP to move faster than ever. You'll learn how to choose exactly the services that best suit your needs, and you'll be able to build applications that run on Google Cloud Platform and start more quickly, suffer fewer disasters, and require less maintenance. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Thousands of developers worldwide trust Google Cloud Platform, and for good reason. With GCP, you can host your applications on the same infrastructure that powers Search, Maps, and the other Google tools you use daily. You get rock-solid reliability, an incredible array of prebuilt services, and a cost-effective, pay-only-for-what-you-use model. This book gets you started. About the Book Google Cloud Platform in Action teaches you how to deploy scalable cloud applications on GCP. Author and Google software engineer JJ Geewax is your guide as you try everything from hosting a simple WordPress web app to commanding cloud-based AI services for computer vision and natural language processing. Along the way, you'll discover how to maximize cloud-based data storage, roll out serverless applications with Cloud Functions, and manage containers with Kubernetes. Broad, deep, and complete, this authoritative book has everything you need. What's inside The many varieties of cloud storage and computing How to make cost-effective choices Hands-on code examples Cloud-based machine learning About the Reader Written for intermediate developers. No prior cloud or GCP experience required. About the Author JJ Geewax is a software engineer at Google, focusing on Google Cloud Platform and API design. Table of Contents PART 1 - GETTING STARTED What is "cloud"? Trying it out: deploying WordPress on Google Cloud The cloud data center PART 2 - STORAGE Cloud SQL: managed relational storage Cloud Datastore: document storage Cloud Spanner: large-scale SQL Cloud Bigtable: large-scale structured data Cloud Storage: object storage PART 3 - COMPUTING Compute Engine: virtual machines Kubernetes Engine: managed Kubernetes clusters App Engine: fully managed applications Cloud Functions: serverless applications Cloud DNS: managed DNS hosting PART 4 - MACHINE LEARNING Cloud Vision: image recognition Cloud Natural Language: text analysis Cloud Speech: audio-to-text conversion Cloud Translation: multilanguage machine translation Cloud Machine Learning Engine: managed machine learning PART 5 - DATA PROCESSING AND ANALYTICS BigQuery: highly scalable data warehouse Cloud Dataflow: large-scale data processing Cloud Pub/Sub: managed event publishing

Download or read book Google Cloud Cookbook written by Rui Costa and published by "O'Reilly Media, Inc.". This book was released on 2021-10-08 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get quick hands-on experience with Google Cloud. This cookbook provides a variety of self-contained recipes that show you how to use Google Cloud services for your enterprise application. Whether you're looking for practical ways to apply microservices, AI, analytics, security, or networking solutions, these recipes take you step-by-step through the process and provide discussions that explain how and why the recipes work. Ideal for system engineers and administrators, developers, network and database administrators, and data analysts, this cookbook helps you get started with Google Cloud regardless of your level of experience. Google veterans Rui Costa and Drew Hodun also cover advanced-level Google Cloud services for those who have appreciable experience with the platform. Learn how to get started with Google Cloud Understand the depth of services Google Cloud provides Gain hands-on experience using practical examples and labs Explore topics that include BigQuery, Cloud Run, and Kubernetes Build and run mobile and web applications on Google Cloud Examine ways to build your cloud applications for scale Build a minimum viable product (MVP) app to use in production Learn data platform and pipeline skills

Download or read book ChatGPT for Enterprise written by Jothi Periasamy and published by Jothi Periasamy. This book was released on 2023-06-29 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: With ChatGPT for Enterprise, large language models (LLM) are integrated into business processes and Generative AI visions become reality. To develop the book, several retail, energy, and education industry case studies were analyzed and explained from concept to implementation. By reading this book, readers will gain a deeper understanding of how to design and build business applications powered by ChatGPT and GPT. To accelerate the implementation of LLM through GPT and ChatGPT modules, we are sharing our GitHub links, as well as steps and procedures for training, testing, tuning, and deploying modules on Google Cloud Platform (GCP). While this book empowers both business and technical users, it is primarily intended for those interested in using CGPT or ChatGPT models in Generative AI or LLM. For professionals and those just getting started with Generative AI and LLM, this book is an excellent starting point for understanding foundational concepts and implementing advanced use cases using Google Cloud Platform.

Download or read book Google Cloud Platform Cookbook written by Legorie Rajan PS and published by Packt Publishing Ltd. This book was released on 2018-04-16 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical recipes to implement cost-effective and scalable cloud solutions for your organization Key Features Implement Google Cloud services in your organization Leverage Google Cloud components to secure your organization’s data A recipe-based guide that promises hands-on experience in deploying a highly scalable and available environment Book Description Google Cloud Platform is a cloud computing platform that offers products and services to host applications using state-of-the art infrastructure and technology. You can build and host applications and websites, store data, and analyze data on Google's scalable infrastructure. This book follows a recipe-based approach, giving you hands-on experience to make the most of Google Cloud services. This book starts with practical recipes that explain how to utilize Google Cloud's common services. Then, you'll see how to make full use of Google Cloud components such as networking, security, management, and developer tools. Next, we'll deep dive into implementing core Google Cloud services into your organization, with practical recipes on App Engine, Compute Engine microservices with Cloud Functions, virtual networks, and Cloud Storage. Later, we'll provide recipes on implementing authentication and security, Cloud APIs, command-line management, deployment management, and the Cloud SDK. Finally, we'll cover administration troubleshooting tasks with the Compute and Container Engines and we'll show how to monitor your organization's efficiency with best practices. By the end of this book, you'll have a complete understanding of how to implement Google Cloud services in your organization with ease. What you will learn Host a Python application on Google Compute Engine Host an application using Google Cloud Functions Migrate a MySQL DB to Cloud Spanner Configure a network for a highly available application on GCP Learn simple image processing using Storage and Cloud Functions Automate security checks using Policy Scanner Understand tools for monitoring a production environment in GCP Learn to manage multiple projects using service accounts Who this book is for This book is for IT professionals, engineers, and developers looking at implementing Google Cloud in their organizations. Administrators and architects planning to make their organization more efficient with Google Cloud will also find this book useful. Basic understanding of Cloud services and the Google Cloud platform is necessary.