Tabla de Contenidos: “…-- Understanding the foundational elements of NEAR -- Learning about the advanced concepts of NEAR -- Transactions and gas -- Data flow -- Tokens and avoiding loss -- Storage options -- Validators and consensus -- NEAR SDK -- Getting started with the NEAR blockchain -- The Contract class -- State and data structures -- Transfers and actions -- Cross contract calls -- NEAR CLI deep dive -- Creating our first project with NEAR -- Understanding the structure and rules of the crossword game -- Setting up the development environment -- Creating a smart contract skeleton -- Testing and deployment -- Interacting with the contract -- Summary -- Part 4: Polkadot and Substrate -- Chapter 9: Exploring Polkadot, Kusama, and Substrate -- Introducing Polkadot -- Interoperability -- Relay chain -- Parathreads -- Bridges -- Accounts -- Transactions -- Tokens and assets -- NFTs -- Understanding the core concepts of PolkaDot -- XCM -- Shared security -- Pallets -- Staking -- Advanced staking concepts -- Main actors -- NPoS election algorithms -- Learning about Kusama -- Governance and on-chain upgrades -- Chaos and experimentation -- Introducing Substrate -- Substrate architecture -- Client and runtime -- Network types -- Node types -- Diving deep into Substrate -- Runtime interfaces -- Core primitives -- FRAME -- Building custom pallets -- Forkless and runtime upgrades -- Consensus -- Summary -- Chapter 10: Hands-On with Substrate -- Technical requirements -- Installing Substrate -- Building our own blockchain -- Starting a local node -- Installing a frontend template -- Starting the frontend template -- Transferring the funds -- Simulating a network -- Starting the first blockchain node -- Adding more nodes…”

“…Image segmentation is a key technology in the field of computer vision, which enables computers to understand the content of an image at a pixel level. …”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright and Credit -- Dedicated -- Table of Contents -- Preface -- Part 1: Understanding the Cybersecurity Relevance of the Vehicle Electrical Architecture -- Chapter 1: Introducing the Vehicle Electrical/Electronic Architecture -- Overview of the basic building blocks of the E/E architecture -- Electronic control units -- Looking at MCU-based ECUs -- Looking at SoC-based ECUs -- Looking inside the MCU and SoC software layers -- ECU domains -- Fuel-based powertrain domain -- Electric drive powertrain domain -- Chassis safety control domain -- Interior cabin domain -- Infotainment and connectivity domain -- Cross-domain -- Exploring the in-vehicle network -- CAN -- FlexRay -- LIN -- UART -- SENT -- GMSL -- I2C -- Ethernet -- J1939 -- Sensors and actuators -- Sensor types -- Actuators -- Exploring the vehicle architecture types -- Highly distributed E/E architecture -- Domain-centralized E/E architecture -- Zone architecture -- Commercial truck architecture types -- Summary -- Answers to discussion points -- Further reading -- Chapter 2: Cybersecurity Basics for Automotive Use Cases -- Exploring the attack classes -- Passive attacks -- Active attacks -- Identifying security objectives -- Integrity -- Authenticity -- Confidentiality -- Accountability -- Availability -- Cryptography applied to automotive use cases -- Building blocks -- One-way hash functions -- Message authentication code algorithms -- Random number generators -- Public key cryptography -- Key management -- NIST defined security strength -- Chinese cryptography -- PQC algorithms -- Security principles -- Defense in depth -- Domain separation -- Least privilege -- Least sharing -- Mediated access -- Protective defaults -- Anomaly detection -- Distributed privilege -- Hierarchical protection and zero trust -- Minimal trusted elements -- Least persistence…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright -- Dedication -- Contributors -- Table of Contents -- Preface -- Part 1: Concepts of Machine Learning -- Chapter 1: Introduction to Machine Learning with Qlik -- Introduction to Qlik tools -- Insight Advisor -- Qlik AutoML -- Advanced Analytics Integration -- Basic statistical concepts with Qlik solutions -- Types of data -- Mean, median, and mode -- Variance -- Standard deviation -- Standardization -- Correlation -- Probability -- Defining a proper sample size and population -- Defining a sample size -- Training and test data in machine learning -- Concepts to analyze model performance and reliability -- Regression model scoring -- Multiclass classification scoring and binary classification scoring -- Feature importance -- Summary -- Chapter 2: Machine Learning Algorithms and Models with Qlik -- Regression models -- Linear regression -- Logistic regression -- Lasso regression -- Clustering algorithms, decision trees, and random forests -- K-means clustering -- ID3 decision tree -- Boosting algorithms and Naive Bayes -- XGBoost -- Gaussian Naive Bayes -- Neural networks, deep learning, and natural-language models -- Summary -- Chapter 3: Data Literacy in a Machine Learning Context -- What is data literacy? …”

“…By the end, you’ll have the expertise to address advanced scenarios, such as working with iframes, and know how TestNG enhances Selenium automation, enabling structured tests, data-driven insights, and swift parallel executions. …”

Tabla de Contenidos: “…Automating LLM interactions -- Lab 4.3 - Generating Splunk SPL content from news -- Summary -- Part 2: Automating Validations within CI/CD Pipelines -- Chapter 5: Implementing Logical Unit Tests -- Technical requirements -- Validating syntax and linting -- Lab 5.1 - CrowdStrike syntax validation -- Performing metadata and taxonomy checks -- Lab 5.2 - Google Chronicle payload validation -- Performing data input checks -- Lab 5.3 - Palo Alto signature limitation tests -- Lab 5.4 - Suricata simulation testing -- Lab 5.5 - Git pre-commit hook protections -- Summary -- Further reading -- Chapter 6: Creating Integration Tests -- Technical requirements -- Mapping and Using Synthetic Payloads -- Lab 6.1 - Splunk SPL Detection Testing -- Testing In-Line Payloads -- Lab 6.2 - AWS CloudTrail Detection Tests -- Executing Live-Fire Asynchronous Tests -- Lab 6.3 - CrowdStrike Falcon Payload Testing -- Lab 6.4 - Deploying Caldera BAS -- Summary -- Further reading -- Chapter 7: Leveraging AI for Testing -- Technical requirements -- Synthetic testing with LLMs -- Lab 7.1 - Poe Bot synthetic CI/CD unit testing -- Evaluating data security and ROI -- Lab 7.2 - CodeRabbit augmented peer review -- Implementing multi-LLM model validation -- Summary -- Part 3: Monitoring Program Effectiveness -- Chapter 8: Monitoring Detection Health -- Technical requirements -- Identifying telemetry sources -- Measuring use case performance -- Upstream detection performance -- Downstream detection performance -- Lab 8.1 - Google Chronicle detection insights -- Extending dashboard use cases -- Lab 8.2 - Mock SOAR disable excessive firing rule -- Summary -- Further reading -- Chapter 9: Measuring Program Efficiency -- Technical requirements -- Creating program KPIs -- Locating data for metrics -- Signal to Noise Ratio -- MITRE ATT&amp -- CK coverage…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright and Credits -- Contributors -- Table of Contents -- Preface -- Part 1: Introduction -- Chapter 1: Why Go? …”

“…Finally, you'll build your own Netflix-like app, integrating video playback functionality with ExoPlayer for both foreground and background operations, and enabling casting to other devices. By the end of this book, you'll have crafted three fully functional projects across multiple platforms and gained the expertise to solve the most common challenges in Android development confidently. …”

“…Generative AI with Amazon Bedrock takes a practical approach to enabling you to accelerate the development and integration of several generative AI use cases in a seamless manner. …”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright and credits -- Foreword -- Contributors -- Table of Contents -- Preface -- Part 1: Understanding the Threat Landscape and Attack Life Cycle -- Chapter 1: Introduction to the Threat Landscape -- Getting familiar with the cyber threat landscape -- Types of threat actors and their motivations -- APTs -- Cybercriminals -- Hacktivists -- Competitors -- Insider threats -- Terrorist groups -- Script kiddies -- Wrapping up -- Building the cyber threat landscape -- Summary -- Chapter 2: Understanding the Attack Life Cycle -- Phase 1 -- gaining an initial foothold…”

Tabla de Contenidos: “…Table of Contents Learning about the Internals of Node.js Dividing Code into Modules and Packages Choosing a Package Manager Using Different Flavors of JavaScript Enhancing Code Quality with Linters and Formatters Building Web Apps with Bundlers Improving Reliability with Testing Tools Publishing npm Packages Structuring Code in Monorepos Integrating Native Code with WebAssembly Using Alternative Runtimes…”

Tabla de Contenidos: “…Table of Contents Introducing Machine Learning and the AWS Machine Learning Stack Exploring Key AWS Machine Learning Services for Healthcare and Life Sciences Machine Learning for Patient Risk Stratification Using Machine Learning to Improve Operational Efficiency for Healthcare Providers Implementing Machine Learning for Healthcare Payors Implementing Machine Learning for Medical Devices and Radiology Images Applying Machine Learning to Genomics Applying Machine Learning to Molecular Data Applying Machine Learning to Clinical Trials and Pharmacovigilance Utilizing Machine Learning in the Pharmaceutical Supply Chain Understanding Common Industry Challenges and Solutions Understanding Current Industry Trends and Future Applications…”

“…La politique budgétaire doit trouver un équilibre entre un resserrement progressif et l'octroi d'un soutien temporaire bien ciblé aux ménages vulnérables à la hausse du coût de la vie, en soutenant la croissance et en répondant aux importants besoins d'investissement. …”

“…While there are plenty of resources for beginners, this book will enable you to uncover the full potential of the tool through sample projects and tutorials. …”

Tabla de Contenidos: “…Table of Contents Introducing Model Serving Introducing Model Serving Patterns Stateless Model Serving Continuous Model Evaluation Keyed Prediction Batch Model Serving Pattern Online Learning Model Serving Two-Phase Model Pattern Pipeline Pattern Model Serving Ensemble Model Serving Pattern Business Logic Pattern Exploring Tensorflow Serving Using Ray Serve Using BentoML Serving ML Models using a Fully Managed Cloud Solution…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright and Credits -- Contributors -- Table of Contents -- Preface -- Part 1: Getting Started with Azure VMware Solution (AVS) -- Chapter 1: Introduction to Azure VMware Solution -- Network connectivity to AVS -- AVS hosts, clusters, and private clouds -- AVS high-level architecture -- Use cases for AVS in an enterprise -- Data center footprint deduction, consolidation, and retirement -- Data center expansion based on demand -- Disaster recovery and business continuity -- Speed and simplification of migration/hybrid cloud -- AVS is very cost-effective -- Enterprise-scale for AVS -- Prerequisites for the implementation of the enterprise-scale landing zone for AVS -- Network and connectivity topologies -- Identity and access management -- Business continuity and disaster recovery -- Design considerations for AVS BC -- Design considerations for AVS DR -- Security, governance, and compliance -- Security -- Governance -- Compliance -- Management and monitoring -- Summary -- Chapter 2: Enterprise-Scale for AVS -- Network and connectivity topology for AVS -- Understanding networking requirements for AVS -- Networking scenarios for AVS with traffic inspection -- Identity and access management for AVS -- vCenter privileges -- Business continuity and disaster recovery -- Design considerations for business continuity in AVS -- The recommended design considerations for business continuity in AVS -- Design considerations for AVS disaster recovery -- Summary -- Part 2: Planning and Deploying AVS -- Chapter 3: Planning for an Azure VMware Solution Deployment -- Subscription identification -- Resource group identification -- Azure region -- Region pairs in Azure -- AVS resource name -- Host size -- Determining the number of hosts and clusters -- Host quota request for AVS -- Requesting a /22 CIDR IP segment for AVS management components…”

“…It automatically maps classes to database tables and enables queries with standard LINQ commands. …”

“…It automatically maps classes to database tables and enables queries with standard LINQ commands. …”

“…Edmon Begoli, Oak Ridge National Laboratory Truly the bible of deep learning…”

“…Martin In Five Lines of Code you will learn: The signs of bad code Improving code safely, even when you don't understand it Balancing optimization and code generality Proper compiler practices The Extract method, Introducing Strategy pattern, and many other refactoring patterns Writing stable code that enables change-by-addition Writing code that needs no comments Real-world practices for great refactoring Improving existing code--refactoring--is one of the most common tasks you'll face as a programmer. …”