Tabla de Contenidos: “…Intro -- Foreword -- Contents -- Part I Join the Geo Revolution -- The Changing Landscape of Geospatial Information Markets -- Introduction -- Rise of the Platforms -- Data as a Service -- Open Data Policies -- New Business Models -- Sensor Use Growing -- Crowdsourcing -- Disruptive Innovation -- Cloud Computing -- Business Models in Cloud Computing -- Microsoft Azure -- Amazon Web Services (AWS) -- Google Cloud Platform -- Conclusion -- References -- The Digital Transformation of Education -- Case Study: How the World Bank Group's Open Learning Campus is Partnering with Earth Observation Satellite Data to Enrich the Learning Experience -- -- Learning as an Accelerator to Achieve Development Goals -- Progress of the OLC so Far -- Flexible Pathways to Learning -- Increasing Importance of Geospatial Data -- Examples of How the OLC is Incorporating Spatial Data -- Issues Relevant to This Experience for the Earth Observation Community -- Case Study Conclusion -- References -- The Open Science Commons for the European Research Area -- Creating the European Research Area: The "Open" Approach -- Problems to Solve -- Lack and/or Incomplete Roadmaps for Research- and e-Infrastructures -- Fragmented Solutions and Policies for Access to Data and Knowledge -- Insufficient Cooperation Between Public and Private Sector -- Lack of National and European Organization Between All Stakeholders -- Many Providers Without a Single Market -- The Open Science Commons -- The European Open Science Cloud -- Open Science Commons for the EOSC -- EOSC Architecture and Services -- Realizing a Federated Approach to Research Data -- Offering of Scalable Access to and Analysis of Research Data for Reuse -- Integrating (Shared) Tools and Applications -- Provisioning of Services for Depositing Data for Resource-Bound Users -- EOSC Service Integration and Management…”

Tabla de Contenidos: “…CRUD operations using Dynamics 365 Web API -- Impersonation in Dynamics 365 Web API -- Retrieving metadata using Web API -- Updates for Web API in Dynamics 365 in version 9.0 -- Summary -- Chapter 8: Leverage Azure Extensions in Dynamics 365 -- Understanding Azure integration with Dynamics 365 -- Introduction to Microsoft Azure Service Bus -- Understanding Dynamics 365 and Azure Service Bus -- Understanding the Azure-aware plugin -- Understanding different contracts between Dynamics 365 and an Azure solution -- Configuring Dynamics 365 and Azure Service Bus integration -- Writing a queue listener -- Writing a topic listener -- Writing a one-way listener -- Writing a two-way listener and an Azure-aware plugin -- Writing a REST listener -- Writing an event hub listener -- Summary -- Chapter 9: Using Editable Grids in Apps -- Overview of Editable Grid in Dynamics 365 -- Prerequisite and security privileges required for configuring Editable Grid -- Entities and views supported by Editable Grid -- Supported out-of-the-box entities -- Web/tablet/phone -- Tablet/phone only -- Web only -- Supported and unsupported data types by Editable Grid -- Configuring editable grids for main entity views -- Configuring editable sub-grid for forms -- Using JavaScript in Editable Grid -- Editable Grid and business rules -- Editable Grid on mobile devices -- Summary -- Chapter 10: Configure Microsoft Cognitive services -- Understanding Microsoft Cognitive Services -- Enabling Dynamics 365 Microsoft Cognitive Services Integration -- Connecting Text Analytics API with Dynamics 365 -- Configuring Knowledge Base Suggestions in Dynamics 365 -- Configuring Similar Records Suggestions in Dynamics 365 -- Configuring Document Suggestions in Dynamics 365 -- Monitoring the Text Analytics Service inside the Azure Portal -- Summary -- Chapter 11: Train the Users through Learning Path…”

Tabla de Contenidos: “…4.3.2 Discovering Jenkins plugins -- 4.4 Baking the Jenkins worker AMI -- Summary -- 5 Discovering Jenkins as code with Terraform -- 5.1 Introducing infrastructure as code -- 5.1.1 Terraform usage -- 5.2 Provisioning an AWS VPC -- 5.2.1 AWS VPC -- 5.2.2 VPC subnets -- 5.2.3 VPC route tables -- 5.2.4 VPC bastion host -- 5.3 Setting up a self-healing Jenkins master -- 5.4 Running Jenkins with native SSL/HTTPS -- 5.5 Dynamically autoscaling the Jenkins worker pool -- 5.5.1 Launch configuration -- 5.5.2 Auto Scaling group -- 5.5.3 Autoscaling scaling policies -- 5.5.4 Workers CPU utilization load -- Summary -- 6 Deploying HA Jenkins on multiple cloud providers -- 6.1 Google Cloud Platform -- 6.1.1 Building Jenkins VM images -- 6.1.2 Configuring a GCP network with Terraform -- 6.1.3 Deploying Jenkins on Google Compute Engine -- 6.1.4 Launching automanaged workers on GCP -- 6.2 Microsoft Azure -- 6.2.1 Building golden Jenkins VM images in Azure -- 6.2.2 Deploying a private virtual network -- 6.2.3 Deploying a Jenkins master virtual machine -- 6.2.4 Applying autoscaling to Jenkins workers -- 6.3 DigitalOcean -- 6.3.1 Creating Jenkins DigitalOcean Snapshots -- 6.3.2 Deploying a Jenkins master Droplet -- 6.3.3 Building Jenkins worker Droplets -- Summary -- Part 3. …”

Tabla de Contenidos: “…Setting Up a Visual Studio Online Account -- Checking Code In and Out -- Undoing Changes -- Shelvesets -- Getting a Specific Version from the Server -- Seeing Changed Items in Solution Explorer -- Looking at History and Comparing Versions -- Labeling -- Interacting with a Team -- Changing Default Source Control Behavior in Visual Studio -- Branching and Merging -- Summary -- Chapter 19 Deploying Your WEBSITE -- Preparing Your Website for Deployment -- Avoiding Hard-Coded Settings -- The Web.config File -- Expression Syntax -- The Web Configuration Manager Class -- Preparing for Deployment -- Microsoft Azure -- Publishing Your Site -- Introducing Web.config Transformations -- Moving Data to a Remote Server -- Smoke Testing Your Application -- Going Forward -- Summary -- Appendix: Answers to Exercises -- Chapter 1 -- Chapter 2 -- Chapter 3 -- Chapter 4 -- Chapter 5 -- Chapter 6 -- Chapter 7 -- Chapter 8 -- Chapter 9 -- Chapter 10 -- Chapter 11 -- Chapter 12 -- Chapter 13 -- Chapter 14 -- Chapter 15 -- Chapter 16 -- Chapter 17 -- Chapter 18 -- Chapter 19 -- Index -- EULA…”

Tabla de Contenidos: “…Create and configure the AWS environment -- Microsoft Azure -- Digital Ocean -- Summary -- Chapter 11: Popular Node.js Web Frameworks -- Koa -- Meteor -- Sails -- Flatiron -- total.js -- LoopBack -- Hapi -- Kick starting Hapi.js -- Scaffolding the Hapi app -- Setting up a server -- Creating APIs -- Creating a configuration-based architecture -- Summary -- Chapter 12: Single Page Applications with Popular Frontend Frameworks -- Why use a frontend framework? …”

Tabla de Contenidos: “…. -- Backup and restore using Microsoft Azure -- Getting ready -- How to do it... -- How it works... -- There's more... -- Chapter 6: Managing Performance -- Introduction -- Explore performance counters with Get-Counter -- Getting ready -- How to do it... -- How it works... -- There's more... -- Explore performance counters using CIM cmdlets -- Getting ready -- How to do it... -- How it works... -- There's more... -- Configuring and using Data Collector Sets -- Getting ready -- How to do it... -- How it works... -- There's more... -- Reporting on performance data -- Getting ready -- How to do it... -- How it works... -- There's more... -- Generating performance monitoring graph -- Getting ready -- How to do it... -- How it works... -- There's more... -- Creating a system diagnostics report -- Getting ready -- How to do it... -- How it works... -- There's more... -- Chapter 7: Troubleshooting Windows Server 2016 -- Introduction -- Checking network connectivity -- Getting ready -- How to do it... -- How it works... -- There's more... -- Using troubleshooting packs -- Getting ready -- How to do it... -- How it works... -- There's more... -- Use best practice analyzer -- Getting ready -- How to do it... -- How it works... -- There's more... -- Managing event logs -- Getting ready -- How to do it... -- How it works... -- There's more... -- Forward event logs to a central server -- Getting ready -- How to do it…”

Tabla de Contenidos: “…1.13.6 Applying Cognition to Develop Health and Wellness -- 1.13.7 Welltok -- 1.13.8 CaféWell Concierge in Action -- 1.14 Advantages of Cognitive Computing -- 1.15 Features of Cognitive Computing -- 1.16 Limitations of Cognitive Computing -- 1.17 Conclusion -- References -- 2 Machine Learning and Big Data in Cyber-Physical System: Methods, Applications and Challenges -- 2.1 Introduction -- 2.2 Cyber-Physical System Architecture -- 2.3 Human-in-the-Loop Cyber-Physical Systems (HiLCPS) -- 2.4 Machine Learning Applications in CPS -- 2.4.1 K-Nearest Neighbors (K-NN) in CPS -- 2.4.2 Support Vector Machine (SVM) in CPS -- 2.4.3 Random Forest (RF) in CPS -- 2.4.4 Decision Trees (DT) in CPS -- 2.4.5 Linear Regression (LR) in CPS -- 2.4.6 Multi-Layer Perceptron (MLP) in CPS -- 2.4.7 Naive Bayes (NB) in CPS -- 2.5 Use of IoT in CPS -- 2.6 Use of Big Data in CPS -- 2.7 Critical Analysis -- 2.8 Conclusion -- References -- 3 HemoSmart: A Non-Invasive Device and Mobile App for Anemia Detection -- 3.1 Introduction -- 3.1.1 Background -- 3.1.2 Research Objectives -- 3.1.3 Research Approach -- 3.1.4 Limitations -- 3.2 Literature Review -- 3.3 Methodology -- 3.3.1 Methodological Approach -- 3.3.2 Methods of Analysis -- 3.4 Results -- 3.4.1 Impact of Project Outcomes -- 3.4.2 Results Obtained During the Methodology -- 3.5 Discussion -- 3.6 Originality and Innovativeness of the Research -- 3.6.1 Validation and Quality Control of Methods -- 3.6.2 Cost-Effectiveness of the Research -- 3.7 Conclusion -- References -- 4 Advanced Cognitive Models and Algorithms -- 4.1 Introduction -- 4.2 Microsoft Azure Cognitive Model -- 4.2.1 AI Services Broaden in Microsoft Azure -- 4.3 IBM Watson Cognitive Analytics -- 4.3.1 Cognitive Computing -- 4.3.2 Defining Cognitive Computing via IBM Watson Interface -- 4.3.3 IBM Watson Analytics -- 4.4 Natural Language Modeling…”

Tabla de Contenidos: “…Debugging a live C# Azure Function, hosted on the Microsoft Azure Cloud environment, using Visual Studio -- Getting ready -- How to do it... -- Deploying Azure Functions in a container -- Getting ready -- Creating an ACR -- How to do it... -- Creating a Docker image for the function app -- Pushing the Docker image to the ACR -- Creating a new function app with Docker -- How it works... -- Chapter 5: Exploring Testing Tools for the Validation of Azure Functions -- Introduction -- Testing Azure Functions -- Getting ready -- How to do it... -- Testing HTTP triggers using Postman -- Testing a Blob trigger using Microsoft Storage Explorer -- Testing the Queue trigger using the Azure Management portal -- There's more... -- Testing an Azure Function on a staged environment using deployment slots -- How to do it... -- There's more... -- Load testing Azure Functions using Azure DevOps -- Getting ready -- How to do it... -- There's more... -- See also -- Creating and testing Azure Functions locally using the Azure CLI tools -- Getting ready -- How to do it... -- Testing and validating Azure Function responsiveness using Application Insights -- Getting ready -- How to do it... -- How it works... -- There's more... -- Developing unit tests for Azure Functions with HTTP triggers -- Getting ready -- How to do it... -- Chapter 6: Monitoring and Troubleshooting Azure Serverless Services -- Introduction -- Troubleshooting your Azure Functions -- How to do it... -- Viewing real-time application logs -- Diagnosing the entire function app -- There's more... -- Integrating Azure Functions with Application Insights -- Getting ready -- How to do it... -- How it works... -- There's more... -- Monitoring your Azure Functions -- How to do it... -- How it works... -- Pushing custom telemetry details to Application Insights Analytics -- Getting ready -- How to do it…”

Tabla de Contenidos: “…-- The public cloud landscape -- Amazon Web Services -- Microsoft Azure -- Google Cloud Platform -- Standing on the shoulders of giants -- A world-class global presence -- Choosing your own adventure -- Leading the way for big data -- The Open Cloud and innovation -- Dedication to customer success -- Bottom-up security -- In good company -- Summary -- Chapter 2: The Google Cloud Console -- Getting started - Google Cloud projects -- Architectural role of Google Cloud projects -- Creating a project -- Free trials on GCP -- The Google Cloud Console -- Understanding the Cloud Console dashboard -- The Google Cloud Shell -- Launching the Cloud Shell -- Supporting multiple sessions -- Features and integrations -- File management -- Web Preview -- The Cloud Shell Code Editor -- Opening in Cloud Shell -- Trying it out -- Installing additional tools -- Boost mode -- Repairing the Cloud Shell -- Other tools -- Mobile apps -- Developer tool integrations -- Summary -- Chapter 3: APIs, CLIs, IAM, and Billing -- Google Cloud APIs -- Managing APIs -- Google APIs Explorer -- Trying out the APIs Explorer -- The Google Cloud SDK -- Installing the Google Cloud SDK -- The gcloud command-line tool -- The basics of gcloud -- Command groups -- Root commands -- Global flags -- Initializing the Google Cloud SDK -- Authentication -- Managing your Google Cloud SDK -- Updating and rollbacks -- Alpha and beta channels -- Configurations in the Google Cloud SDK -- Modifying configuration properties -- Multiple configurations -- Other command-line tools -- bq -- gsutil -- kubectl -- Automating tasks with gcloud -- Modifying output and behavior -- Formatting attributes -- Formatting projections -- Filtering -- Google Cloud IAM -- How IAM works…”

Tabla de Contenidos: “…. -- See also -- Debugging live C# Azure Function hosted on the Microsoft Azure Cloud environment using Visual Studio -- Getting ready…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright and Credits -- Dedications -- Contributors -- Table of Contents -- Part 1: Migrating to the Cloud -- Chapter 1: Introduction to Cloud Transformation -- Introduction to the cloud -- The origins of cloud computing -- Key characteristics of cloud computing -- On-demand self-service -- Wide range of network access -- Multi-tenant model and resource pooling -- Rapid elasticity -- PAYG model -- Measured service and reporting -- Understanding the motivators for cloud adoption -- Resilience -- Advanced security -- Carbon footprint reduction -- Improved optimization and efficiency -- Faster innovation and business agility -- Understanding CSPs -- Amazon Web Services (AWS) -- Microsoft Azure -- Google Cloud Platform -- Alibaba Cloud -- Exploring the service models - SaaS, PaaS, and IaaS -- Infrastructure as a Service (IaaS) -- Platform as a Service (PaaS) -- Software as a service (SaaS) -- Exploring the deployment models - public, private, hybrid, multi, and community -- The public cloud -- The private cloud -- The hybrid cloud -- Multi-cloud -- The community cloud -- Comparison between the different cloud deployment models -- Summary -- Further reading -- Chapter 2: Understanding Cloud Migration -- Cloud migration - key concepts and fundamentals -- What is cloud migration? …”

Tabla de Contenidos: “…Technical sophistication in language applications -- Challenges and considerations in implementation -- Azure Open AI Service: An in-depth technical exploration -- Foundational integration with Microsoft Azure -- Operational mechanics of Azure Open AI Service -- Enhancing AI performance in the cloud -- Security, compliance, and ethical considerations -- Integrating language models and ChatGPT with Dynamics 365 AI -- Detailed integration process -- Architectural foundations of integration -- Enhancing Dynamics 365 with AI capabilities -- Addressing implementation challenges -- Future enhancements and evolutions -- Real-world use cases and implementation examples of integrating language models and ChatGPT with Dynamics 365 AI -- Use case 1 - Multinational retail chain enhances customer experience -- Use case 2 - Finance consulting firm leverages AI for market analysis -- Use case 3 - Global corporation streamlines HR operations -- Summary -- Questions -- Answers -- Chapter 8: Harnessing MS Copilot for Enhanced Business Insights -- Overview of MS Copilot and its comprehensive features -- Advanced data processing and analysis -- The integration of cutting-edge AI technologies -- Enhancing business intelligence -- User experience and interface design -- Real-time interaction and automated customer support -- Integrating MS Copilot with Dynamics 365 AI -- Harmonizing advanced technologies -- Enhancing Dynamics 365 with AI -- Best practices and real-world integration scenarios -- Transforming business operations and development -- Leveraging MS Copilot for code generation and optimization in Dynamics 365 AI -- Case studies in harnessing MS Copilot for enhanced business insights -- Case study 1 - revolutionizing retail with personalized customer experiences -- Case study 2 - enhancing healthcare services with predictive analytics…”

Tabla de Contenidos: “…Data that is not pre-embedded -- Chains -- Agents -- Long-term memory and referring to prior conversations -- Ensuring continuous relevance through incremental updates and automated monitoring -- Reviewing a simple LangChain setup in a Jupyter notebook -- Setting up a LangChain pipeline with Python -- LLMs in the cloud -- AWS -- Microsoft Azure -- GCP -- Concluding cloud services -- Summary -- Chapter 9: Exploring the Frontiers: Advanced Applications and Innovations Driven by LLMs -- Technical requirements -- Enhancing LLM performance with RAG and LangChain - a dive into advanced functionalities -- LangChain pipeline with Python - enhancing performance with LLMs -- Advanced methods with chains -- Asking the LLM a general knowledge question -- Requesting output structure - making the LLM provide output in a particular data format -- Evolving to a fluent conversation - inserting an element of memory to have previous interactions as reference and context for follow-up prompts -- Retrieving information from various web sources automatically -- Retrieving content from a YouTube video and summarizing it -- Prompt compression and API cost reduction -- Prompt compression -- Experimenting with prompt compression and evaluating trade-offs -- Multiple agents - forming a team of LLMs that collaborate -- Potential advantages of multiple LLM agents working simultaneously -- Concluding thoughts on the multiple-agent team -- Summary -- Chapter 10: Riding the Wave: Analyzing Past, Present, and Future Trends Shaped by LLMs and AI -- Key technical trends around LLMs and AI -- Computation power - the engine behind LLMs -- The future of computational power in NLP -- Large datasets and their indelible mark on NLP and LLMs -- Purpose - training, benchmarking, and domain expertise -- Value - robustness, diversity, and efficiency…”

Tabla de Contenidos: “…Calling a flow within Power Apps -- Lab 12 -- Activity 1: Creating a flow for when a new grocery is added -- Activity 2: Adding the flow to the app -- Activity 3: Creating a reminder flow -- Summary -- Questions -- Further reading -- Chapter 15: Using Azure with Power Apps -- Technical requirements -- Introducing Microsoft Azure -- Integrating with Azure Active Directory (AAD) -- Implementing Azure Automation -- Creating an Azure Automation account -- Preparing your Azure Automation account for use -- Installing modules -- Storing credentials -- Storing variables -- Creating runbooks -- Using Azure Automation in Power Apps -- Calling CreateJob -- Getting the job's output -- Using Azure Functions -- Using a queue -- Creating an function -- Summary -- Questions -- Further reading -- Chapter 16: Visualizing Data -- Technical requirements -- The use of data -- Using chart controls -- Using a column chart -- Using a line chart -- Using a pie chart -- Embedding Power BI in your app -- A brief intro to Power BI -- Creating a basic report -- Embedding the report into your canvas app -- Lab 13 -- Activity 1 - Formatting the data -- Activity 2 - Displaying the chart -- Summary -- Further reading -- Chapter 17: Introducing Artificial Intelligence -- Technical requirements -- What is AI Builder? …”

“…New cloud integrations covered in this book include Microsoft Azure Purview and the use of Azure SQL for high availability and disaster recovery. …”

Tabla de Contenidos: “…-- Pure-play public cloud strategy -- Public cloud benefits -- Need for agility -- Ability to experiment without upfront cost -- Reducing operational overheads -- Ability to consume enhanced services -- Shortcomings of a public cloud -- Cost -- Control/customizability -- Compliance -- Fear of lock-in -- Hybrid cloud case study -- Summary - maximizing benefits -- Chapter 3: Hybrid Cloud Building Blocks -- The story of a web application -- Transport level -- Case 1 - without a proxy -- Case 2 - with a proxy -- Application level -- Web tier -- Application tier -- Database tier -- Putting it all together -- Use cases of a hybrid cloud -- Isolated use case -- Distributed use case -- Co-Existent use case -- Cloud bursting -- Using cognitive services -- Supporting application use cases -- Backup and disaster recovery in the cloud -- Decoupling the tiers -- Case in point - architecture of OpenStack -- Services to enable a hybrid cloud -- Network connectivity -- DNS service -- Public cloud services for hybrid deployment -- Amazon Web Services (AWS) -- Storage gateway -- Direct connect -- Route 53 -- Amazon EC2 run command -- VMware cloud on AWS -- Microsoft Azure -- Azure Stack -- Azure Site Recovery (ASR) -- Azure Traffic Manager -- Summary - setting up hybrid cloud -- Chapter 4: Architecting the Underpinning Services -- Networking -- Underlay network…”

Tabla de Contenidos: “…-- Automated deployment options -- Scripting -- Azure Resource Manager -- Initial configuration -- Initial configuration with the Custom Script Extension -- Initial configuration with cloud-init -- Vagrant and Packer -- Installing and configuring Vagrant -- Deploying a virtual machine with Vagrant -- Vagrant provisioners -- Packer (part 1) -- Installing and configuring Packer -- Custom images and VHDs -- Creating a managed image -- Alternative method using snapshots -- Packer (part 2) -- Custom VHDs -- Summary -- Questions -- Further reading -- Chapter 8: Exploring Continuous Configuration Automation -- Technical requirements -- Ansible -- Installation of Ansible -- SSH configuration -- Bare-minimum configuration -- Inventory file -- Ansible playbooks and modules -- Conditionals - when statement -- Loops -- Handlers -- Working with variables -- Working with templates -- Authenticating to Microsoft Azure -- Resource group -- Virtual machine -- Azure inventory management in Ansible -- SaltStack -- Some Salt terminology -- SaltStack installation -- Authorization -- Execution modules -- Salt states -- Top file -- Salt grains -- State conditions -- Working with variables and templates -- Integration with Azure -- PowerShell desired state configuration -- Azure automation DSC -- Automation account -- Installing PowerShell DSC on Linux -- Creating a desired state -- PowerShell DSC Resources -- Applying the resources in Azure -- Other solutions -- Summary -- Questions -- Further reading…”

Tabla de Contenidos: “…Monitoring and troubleshooting jobs -- Alerts -- Summary -- Chapter 10: Always On High Availability Features -- Installing Windows Server Failover Cluster -- Always On Failover Cluster Instances -- Adding nodes to the SQL Server Failover Cluster -- Initiating a failover -- Always On Availability Groups -- Configuring Always On Availability Groups -- Creating an Availability Group -- Failover and monitoring -- Basic Availability Groups -- Distributed Availability Groups -- Summary -- Chapter 11: In-Memory OLTP - Why and How to Use it -- In-Memory OLTP architecture -- Data storage differences in OLTP -- Request processing differences in OLTP -- Cooperation of disk-based and memory-based parts of SQL Server -- In-Memory OLTP limitations -- Creating In-Memory tables and natively compiled stored procedures -- Preparing for In-Memory OLTP -- Creating In-Memory OLTP objects -- Creating tables with indexes -- Natively compiled stored procedures -- Migrating disk-based objects to In-Memory OLTP -- Monitoring In-Memory OLTP -- In-Memory OLTP usage scenarios -- Assignment of the user story sample -- Example 1 - inserting incoming data into In-Memory tables -- Example 2 - updating data in an In-Memory table -- Example 3 - improving real-time analytics -- Summary -- Chapter 12: Combining SQL Server 2017 with Azure -- Overview of data related technologies in Microsoft Azure -- Understanding Azure SQL database -- Starting with Azure portal -- Creating the Azure SQL database -- Understanding Azure SQL Server -- Creating Azure SQL Server -- Using Azure SQL Server -- Azure SQL Data Warehouse -- Creating Azure SQL Data Warehouse -- Using Azure SQL Data Warehouse -- Microsoft SQL Server 2017 and hybrid scenarios -- StretchDB -- Data files in Azure -- Backups to Azure -- Managed backup to Azure -- Backup to a URL -- Snapshot backups -- Summary -- Index…”

Tabla de Contenidos: “…-- Motifs and Discords -- Subsequences and Matches -- Discretizing the Data -- Implementing SAX -- Segmentation and Blocking -- Making SAX Multi-series -- Scoring Outliers -- Test and Website Updates -- Unit and Integration Tests -- Website Updates -- Conclusion -- Part V: Stacking Up to the Competition -- Chapter 18: Configuring Azure Cognitive Services Anomaly Detector -- Gathering Market Intelligence -- Amazon Web Services: SageMaker -- Microsoft Azure: Cognitive Services -- Google Cloud: AI Services -- Configuring Azure Cognitive Services -- Set Up an Account -- Using the Demo Application -- Conclusion -- Chapter 19: Performing a Bake-Off -- Preparing the Comparison…”

Tabla de Contenidos: “…4.3.1.1 Private Cloud -- 4.3.1.2 Public Cloud -- 4.3.1.3 Hybrid Cloud -- 4.3.1.4 Community Cloud -- 4.3.2 Service Models for Cloud Computing -- 4.3.2.1 Software as a Service (SaaS) -- 4.3.2.2 Platform as a Service (PaaS) -- 4.3.2.3 Infrastructure as a Service (IaaS) -- 4.3.3 Data Analytics on Cloud -- 4.4 Cloud-Based IoT Data Analytics Platform -- 4.4.1 Atos Codex -- 4.4.2 AWS IoT -- 4.4.3 IBM Watson IoT -- 4.4.4 Hitachi Vantara Pentaho, Lumada -- 4.4.5 Microsoft Azure IoT -- 4.4.6 Oracle IoT Cloud Services -- 4.5 Machine Learning for IoT Analytics in Cloud -- 4.5.1 ML Algorithms for Data Analytics -- 4.5.2 Types of Predictions Supported by ML and Cloud -- 4.6 Challenges for Analytics Using Cloud -- 4.7 Conclusion -- References -- Chapter 5 Deep Learning Architectures for IoT Data Analytics -- 5.1 Introduction -- 5.1.1 Types of Learning Algorithms -- 5.1.1.1 Supervised Learning -- 5.1.1.2 Unsupervised Learning -- 5.1.1.3 Semi-Supervised Learning -- 5.1.1.4 Reinforcement Learning -- 5.1.2 Steps Involved in Solving a Problem -- 5.1.2.1 Basic Terminology -- 5.1.2.2 Training Process -- 5.1.3 Modeling in Data Science -- 5.1.3.1 Generative -- 5.1.3.2 Discriminative -- 5.1.4 Why DL and IoT? …”