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Google Cloud Run for DevOps: Automating Deployments and Scaling by Robert Johnson
English | February 2, 2025 | ISBN: N/A | ASIN: B0DVS15TKW | 393 pages | EPUB | 0.64 Mb
This book offers a comprehensive guide for professionals and developers seeking to master Google Cloud Run for DevOps. It covers essential topics ranging from setting up a robust development environment and containerizing applications to deploying with advanced CI/CD pipelines, scaling dynamically, and ensuring robust security. Each chapter provides detailed, hands-on strategies designed to integrate modern deployment practices and enhance operational efficiency in a serverless framework.

Structured to build upon core concepts progressively, the book also addresses monitoring and troubleshooting, cost optimization, and emerging trends within the evolving cloud ecosystem. With practical examples and best practices throughout, it equips readers with the necessary tools and insights to streamline deployments, manage resources effectively, and remain at the forefront of cloud-native technologies.



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Governing Digital Mental Health: Introducing the 5P Model and the Digital Behavioral Health Expert (SpringerBriefs in Public Health) by Juan Joseacute
English | July 16, 2025 | ISBN: 3031947622 | 146 pages | Epub PDF (True) | 3.95 Mb
This book presents a bold governance blueprint for an era in which mental health systems face a historic transition: as care delivery becomes increasingly shaped by code, platforms, and predictive algorithms, new governance frameworks are needed to protect equity, ethics, and human-centered leadership. At the core of this blueprint is the 5P Model - Predictive, Preventive, Personalized, Participatory, and Precision-based - a transformative framework for building equitable, effective behavioral health systems in the age of AI.

The book introduces the Digital Behavioral Health Expert (DBHE), a new professional role designed to bridge clinical care, policy systems, and digital infrastructure. Unlike traditional mental health models that focus on professional interaction alone, the DBHE enables coordination across platforms, stakeholders, and jurisdictions - turning governance into a strategic, ethical, and human-centered function.
Designed for stakeholders across the ecosystem - policymakers shaping regulation, managers implementing care systems, clinicians navigating hybrid models, developers building ethical tools, and investors backing scalable solutions - this book equips each with strategic insight for a digitally governed future of mental health.
"A timely vision for ethical, inclusive governance in digital mental health."
- Professor Anil Thapliyal, Executive Director, eMental Health International Collaborative (eMHIC)



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Grammar, Punctuation and Sentences by Helen Bolam
English | July 13, 2020 | ISBN: N/A | ASIN: B08CXVYGJF | 117 pages | EPUB | 0.23 Mb
English Grammar Simplified

Grammar, Punctuation and Sentences is an ideal tool for anyone who wants to produce clear, concise, and grammatically correct writing of a high standard. Whether you're writing professional documents, personal letters emails, or school papers, you'll discover this book is indispensable. From verbs, and nouns, to sentence creation, writer Helen Bolam guides you through this clear guide. Enabling you to get your thoughts out in an uncomplicated way.
Grammar, Punctuation and Sentences is a quick concise guide to grammar, punctuation and the use of sentences in English grammar. An easy-to-read resource with clear explanations of grammar, punctuation and sentences.
What's included in the book:
Introduction
Grammar
Why Grammar is so Important
What You Need to Know About Nouns, Verbs and Gerunds
Pronouns, Prepositions, Adjectives and Adverbs: Parts of Speech
Understanding Infinitives
Subjects and Verbs, What are They?
What You Need to Know About Verbs, Clauses and Phrases?
Capitalisation and Numbers
The Rules of Capitalisation
Rules for Writing Numbers
Punctuation
The Secret to Flawless Punctuation
Acronyms, Contractions, Initialisms, and Shortenings: What You Need to Know About Abbreviations
Sentences
What You Need to Know About the Function of Syntax in Sentences
Diction in Sentences
What You Need to Know About Sentences
The Five Elements of a Sentence
Simple, Compound and Complex Sentences
How to Construct a Really Good Sentence
Sentence Linking: Essential Strategies to Solve Your Sentence Problems
Using Punctuation in Sentence Combinations
How to Fine Tune a Sentence
Making Improvements to a Sentence at Word Level (Part 1)
Making Improvements to a Sentence at Word Level (Part 2)
Words That Confuse
Homophones: The Words that Puzzle Everybody
Resources and Tools
Grammar Resources
Afterword
Make learning English grammar more straightforward with this simple guide.




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Grammarly API Integration with C#: Build Smart Writing Tools: A Developer's Guide to Leveraging Grammarly API in C# Applications for Real-Time Grammar, Style, and Tone Analysis by BOSCO-IT CONSULTING
English | March 28, 2025 | ISBN: N/A | ASIN: B0F2ZGR84Q | 340 pages | EPUB | 0.45 Mb
In today's fast-paced digital world, communication is critical - and clear, error-free writing can make all the difference. Whether you are building productivity tools, educational software, custom editors, or enterprise platforms, integrating advanced language correction features into your C# applications offers immense value to end users. Grammarly API Integration with C#: Build Smart Writing Tools is the ultimate guide for developers seeking to harness Grammarly's powerful capabilities within .NET environments.

This book takes you deep into the practical aspects of building intelligent grammar-checking features into your own desktop and web-based applications using C#. You will learn how to connect to Grammarly's WebSocket-based API (unofficial), send and receive data in real time, interpret responses, and build tools that rival commercial software in functionality. Whether you are a solo developer or part of a larger team, this book equips you with everything you need to create dynamic, AI-powered writing assistants.
Inside, you will find step-by-step instructions on how to establish a WebSocket connection with Grammarly, format and send text payloads, handle API responses, and incorporate the results into real-time editors and applications. You'll also learn how to manage multiple users, store suggestions, implement one-click correction features, and design user-friendly grammar feedback interfaces.
The book goes beyond technical implementation by helping you understand real-world use cases, best practices for writing tools, and how Grammarly compares to other natural language processing (NLP) services. You'll explore ways to integrate Grammarly alongside Microsoft Cognitive Services, OpenAI, and LanguageTool for even more advanced functionality.
What makes this book unique is its strong focus on C# and .NET developers. You will find clear, actionable code examples tailored to Visual Studio, including console applications, WPF interfaces, and ASP.NET setups. From handling WebSocket events to building browser extension-like experiences, each chapter is filled with hands-on examples that help you bring ideas to life.
This book covers:Setting up a C# development environment for Grammarly integrationUnderstanding Grammarly's capabilities, limitations, and API behaviorEstablishing a WebSocket connection and sending real-time dataParsing grammar, spelling, tone, and clarity feedback from the APIBuilding custom grammar-checking tools in WinForms or WPFProviding interactive suggestions and automated correctionsCreating browser-style feedback within desktop applicationsSupporting multiple users and maintaining session stateIdeal for C# developers, software engineers, tech entrepreneurs, and product builders, this guide will help you create innovative, user-friendly writing support tools that deliver real value. Whether your goal is to build a writing assistant for students, a business communication enhancer, or a collaborative team editor, this book gives you the structure and skills to succeed.
If you have ever wanted to offer Grammarly-like functionality inside your own applications - and do it in a reliable, professional way using the tools you already know - this book is for you.
Perfect for:C# developers looking to integrate grammar checking featuresEngineers building real-time chat, messaging, or email platformsEducators or edtech creators developing writing improvement toolsBy the end of this book, you will be able to implement a grammar-checking engine that helps users write better, with real-time suggestions, correction features, and seamless language enhancements - all directly from your C# environment.




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Granular, Fuzzy, and Soft Computing (Encyclopedia of Complexity and Systems Science Series) by Tsau-Young Lin, Churn-Jung Liau, Janusz Kacprzyk
English | March 30, 2023 | ISBN: 1071626272 | 964 pages | MOBI | 93 Mb
The first edition of the Encyclopedia of Complexity and Systems Science (ECSS, 2009) presented a comprehensive overview of granular computing (GrC) broadly divided into several categories: Granular computing from rough set theory, Granular Computing in Database Theory, Granular Computing in Social Networks, Granular Computing and Fuzzy Set Theory, Grid/Cloud Computing, as well as general issues in granular computing. In 2011, the formal theory of GrC was established, providing an adequate infrastructure to support revolutionary new approaches to computer/data science, including the challenges presented by so-called big data.

For this volume of ECSS, Second Edition, many entries have been updated to capture these new developments, together with new chapters on such topics as data clustering, outliers in data mining, qualitative fuzzy sets, and information flow analysis for security applications. Granulations can be seen as a natural and ancient methodology deeply rooted in the human mind. Many daily "things" are routinely granulated into sub "things": The topography of earth is granulated into hills, plateaus, etc., space and time are granulated into infinitesimal granules, and a circle is granulated into polygons of infinitesimal sides. Such granules led to the invention of calculus, topology and non-standard analysis. Formalization of general granulation was difficult but, as shown in this volume, great progress has been made in combing discrete and continuous mathematics under one roof for a broad range of applications in data science.



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Graph Drawing Software by Michael Jünger, Petra Mutzel
English | PDF (True) | 2004 | 381 Pages | ISBN : 3540008810 | 37 MB
Automatic Graph Drawing is concerned with the layout of relational structures as they occur in Computer Science (Data Base Design, Data Mining, Web Mining), Bioinformatics (Metabolic Networks), Businessinformatics (Organization Diagrams, Event Driven Process Chains), or the Social Sciences (Social Networks).

xGraph Drawing Software

Close
Graph Drawing Software by Michael Jünger, Petra Mutzel
English | PDF (True) | 2004 | 381 Pages | ISBN : 3540008810 | 37 MB
Automatic Graph Drawing is concerned with the layout of relational structures as they occur in Computer Science (Data Base Design, Data Mining, Web Mining), Bioinformatics (Metabolic Networks), Businessinformatics (Organization Diagrams, Event Driven Process Chains), or the Social Sciences (Social Networks).
In mathematical terms, such relational structures are modeled as graphs or more general objects such as hypergraphs, clustered graphs, or compound graphs. A variety of layout algorithms that are based on graph theoretical foundations have been developed in the last two decades and implemented in software systems.
After an introduction to the subject area and a concise treatment of the technical foundations for the subsequent chapters, this book features 14 chapters on state-of-the-art graph drawing software systems, ranging from general "tool boxes'' to customized software for various applications. These chapters are written by leading experts, they follow a uniform scheme and can be read independently from each other.
[/b]



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Graph Drawing Software by Michael Jünger, Petra Mutzel
English | PDF (True) | 2004 | 381 Pages | ISBN : 3540008810 | 37 MB
Automatic Graph Drawing is concerned with the layout of relational structures as they occur in Computer Science (Data Base Design, Data Mining, Web Mining), Bioinformatics (Metabolic Networks), Businessinformatics (Organization Diagrams, Event Driven Process Chains), or the Social Sciences (Social Networks).

xGraph Drawing Software

Close
Graph Drawing Software by Michael Jünger, Petra Mutzel
English | PDF (True) | 2004 | 381 Pages | ISBN : 3540008810 | 37 MB
Automatic Graph Drawing is concerned with the layout of relational structures as they occur in Computer Science (Data Base Design, Data Mining, Web Mining), Bioinformatics (Metabolic Networks), Businessinformatics (Organization Diagrams, Event Driven Process Chains), or the Social Sciences (Social Networks).
In mathematical terms, such relational structures are modeled as graphs or more general objects such as hypergraphs, clustered graphs, or compound graphs. A variety of layout algorithms that are based on graph theoretical foundations have been developed in the last two decades and implemented in software systems.
After an introduction to the subject area and a concise treatment of the technical foundations for the subsequent chapters, this book features 14 chapters on state-of-the-art graph drawing software systems, ranging from general "tool boxes'' to customized software for various applications. These chapters are written by leading experts, they follow a uniform scheme and can be read independently from each other.
[/b]



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Graph Machine Learning: Learn about the latest advancements in graph data to build robust machine learning models - 2nd Edition
English | 2025 | ISBN: 1803248068 | 537 pages | True EPUB | 16.59 MB
Enhance your data science skills with this updated edition featuring new chapters on LLMs, temporal graphs, and updated examples with modern frameworks, including PyTorch Geometric, and DGL
Key Features:


- Master new graph ML techniques through updated examples using PyTorch Geometric and Deep Graph Library (DGL)
- Explore GML frameworks and their main characteristics
- Leverage LLMs for machine learning on graphs and learn about temporal learning
Book Description:

Graph Machine Learning, Second Edition builds on its predecessor's success, delivering the latest tools and techniques for this rapidly evolving field. From basic graph theory to advanced ML models, you'll learn how to represent data as graphs to uncover hidden patterns and relationships, with practical implementation emphasized through refreshed code examples. This thoroughly updated edition replaces outdated examples with modern alternatives such as PyTorch and DGL, available on GitHub to support enhanced learning.
The book also introduces new chapters on large language models and temporal graph learning, along with deeper insights into modern graph ML frameworks. Rather than serving as a step-by-step tutorial, it focuses on equipping you with fundamental problem-solving approaches that remain valuable even as specific technologies evolve. You will have a clear framework for assessing and selecting the right tools.
By the end of this book, you'll gain both a solid understanding of graph machine learning theory and the skills to apply it to real-world challenges.
What You Will Learn:

- Implement graph ML algorithms with examples in StellarGraph, PyTorch Geometric, and DGL
- Apply graph analysis to dynamic datasets using temporal graph ML
- Enhance NLP and text analytics with graph-based techniques
- Solve complex real-world problems with graph machine learning
- Build and scale graph-powered ML applications effectively
- Deploy and scale your application seamlessly
Who this book is for:

This book is for data scientists, ML professionals, and graph specialists looking to deepen their knowledge of graph data analysis or expand their machine learning toolkit. Prior knowledge of Python and basic machine learning principles is recommended.



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Graph Machine Learning: Learn about the latest advancements in graph data to build robust machine learning models - 2nd Edition
English | 2025 | ISBN: 1803248068 | 435 pages | True PDF | 14.13 MB
Enhance your data science skills with this updated edition featuring new chapters on LLMs, temporal graphs, and updated examples with modern frameworks, including PyTorch Geometric, and DGL

Key Features:
- Master new graph ML techniques through updated examples using PyTorch Geometric and Deep Graph Library (DGL)
- Explore GML frameworks and their main characteristics
- Leverage LLMs for machine learning on graphs and learn about temporal learning
Book Description:
Graph Machine Learning, Second Edition builds on its predecessor's success, delivering the latest tools and techniques for this rapidly evolving field. From basic graph theory to advanced ML models, you'll learn how to represent data as graphs to uncover hidden patterns and relationships, with practical implementation emphasized through refreshed code examples. This thoroughly updated edition replaces outdated examples with modern alternatives such as PyTorch and DGL, available on GitHub to support enhanced learning.
The book also introduces new chapters on large language models and temporal graph learning, along with deeper insights into modern graph ML frameworks. Rather than serving as a step-by-step tutorial, it focuses on equipping you with fundamental problem-solving approaches that remain valuable even as specific technologies evolve. You will have a clear framework for assessing and selecting the right tools.
By the end of this book, you'll gain both a solid understanding of graph machine learning theory and the skills to apply it to real-world challenges.
What You Will Learn:
- Implement graph ML algorithms with examples in StellarGraph, PyTorch Geometric, and DGL
- Apply graph analysis to dynamic datasets using temporal graph ML
- Enhance NLP and text analytics with graph-based techniques
- Solve complex real-world problems with graph machine learning
- Build and scale graph-powered ML applications effectively
- Deploy and scale your application seamlessly
Who this book is for:
This book is for data scientists, ML professionals, and graph specialists looking to deepen their knowledge of graph data analysis or expand their machine learning toolkit. Prior knowledge of Python and basic machine learning principles is recommended.



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Graph Machine Learning - Second Edition (Early Access)
English | 2024 | ISBN: 9781803248066 | 329 pages | MOBI | 4.52 Mb
Explore the updated edition with new chapters on LLMs, Temporal Graphs, and updated Pytorch Geometric examples to enhance your data science skills.

Key Features
Master new graph ML techniques with updated Pytorch Geometric examples
Explore case studies that demonstrate real-world applications of GML
Leverage graphs for advanced tasks in LLMs and Temporal learning
Book Description
Graph Machine Learning, Second Edition not only revises but expands on its successful first edition, providing you with the latest tools and techniques in graph machine learning. This edition introduces comprehensive updates across all chapters, new chapters on trending topics like LLMs and Temporal Graph Learning, and real-world case studies that illustrate the practical applications of these concepts.
From basic graph theory to advanced machine learning models, the book guides you through understanding how data can be represented as graphs to uncover complex patterns and relationships hidden in your data. This edition emphasizes practical application with updated code examples using Pytorch Geometric, making it easier for you to implement what you learn.
The expanded content includes detailed chapters on using graph machine learning for dynamic and evolving data and integrating graph theory with Large Language Models (LLMs) for enriched data interaction and analysis. By the end of this book, you'll not only be versed in the theory of graph machine learning but also adept at applying it to solve real challenges in innovative ways.
What you will learn
Implement graph ML algorithms with some examples in PyTorch Geometric
Apply graph analysis to dynamic datasets using Temporal Graph ML
Enhance NLP and text analytics with graph-based techniques
Solve complex real-world problems with graph machine learning
Build and scale graph-powered ML applications effectively
Deploy and scale out your application seamlessly
Who this book is for
This book is ideal for data scientists, ML professionals, and graph specialists looking to deepen their knowledge of graph data analysis or expand their machine learning toolkit. Prior knowledge of Python and basic machine learning principles is recommended.



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Great American Public Companies: The greatest companies of the S&P 500 by Alex Bugeja
English | December 21, 2024 | ISBN: N/A | ASIN: B0DR77MPPJ | 199 pages | EPUB | 1.24 Mb
Dive into the fascinating stories of 25 of America's greatest public companies, each a titan in its respective field. From tech giants like Apple, Microsoft, and Alphabet, to healthcare behemoths like Johnson & Johnson and UnitedHealth Group, this book explores the journeys of companies that have not only shaped industries but have also revolutionized the way we live, work, and interact with the world. Discover the secrets behind their innovation, resilience, and growth, from the early days of personal computing to the rise of cloud computing, e-commerce, and artificial intelligence.

Beyond the tech sector, this book delves into the histories of financial powerhouses like JPMorgan Chase and Visa, consumer goods icons like Coca-Cola and Walmart, and energy giants like Exxon Mobil and Chevron. Each chapter offers an in-depth look at a single company, providing a comprehensive study of its evolution, challenges, and triumphs. Learn about their groundbreaking products, explore the impact of visionary leaders, and understand the strategies that propelled these companies to the top of the S&P 500.
More than just a collection of corporate histories, this book provides a captivating glimpse into the American spirit of enterprise and innovation. Explore the common threads that weave through these diverse stories: a relentless focus on customer needs, a commitment to adaptability, and the power of groundbreaking innovation. Gain a deeper understanding of the forces that shape our world and the dynamic interplay between business, technology, and the American economy.




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Great Australian Volunteer Surf Life Saving Stories (Great Australian Stories) by Bill Marsh
English | July 1, 2025 | ISBN: 1460715888 | 334 pages | EPUB | 3.36 Mb
After I'd got him out of harm's way, I dived back in yet again and swam out past the surf-break, out to where the other two lads were floundering. Then, one at a time, I took them back onto the rocks - all done against the raging rip and wild surf. By then an hour or so had passed. Still, severe cuts, bruises and abrasions aside, I'd successfully saved the lives of the four young people who, in all probability, would've otherwise drowned.

Surf Life Saving Australia is the nation's largest volunteer organisation, with over 300 affiliated clubs and more than 198,000 members - that's 198,000 Australians each with amazing stories to tell.
From the golden sands of Bondi to the remote coastlines of Arnhem Land and the chilly waters of Tasmania, Bill 'Swampy' Marsh has gathered some of the best of those stories - from acts of remarkable bravery and daring rescues against the odds, to lighthearted and humorous yarns of encounters with crocodiles and sharks. Each story shines a light on the unwavering dedication, community spirit and extraordinary experiences of everyday Australians who selflessly devote their time to protect others.
Filled with courage, humour, heartache and joy, Great Australian Volunteer Surf Life Saving Stories shows that the power of the ocean is matched only by the hearts of those who guard its shores.



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