Books

In this book you will learn all the details of the RP2040 microcontroller (used in the Raspberry Pi Pico and other boards) and how to leverage them in amazing applications.

Master the ideas behind Java concurrency, from threads, race conditions, and synchronization to CompletableFuture, virtual threads, and structured concurrency. With practical patterns, runnable examples, and a companion GitHub repository, this book helps you move from understanding concurrency to applying it in real programs.

Learn Python through annotated diagrams, worked examples and practical projects—from variables and loops to pandas, classes and data preparation. Includes the updated 79-page PDF and fixed-layout EPUB.

This book is for cross-functional teams working in an iterative delivery environment, planning with user stories and testing frequently changing software under tough time pressure. This book will help you test your software better, easier and faster. Many of these ideas also help teams engage their business stakeholders better in defining key expectations and improve the quality of their software products.

Conquer the "Algorithm Wall" with 20 high-density practical questions. Learn the logical thinking and pseudocode mastery required to pass the most challenging part of the FE exam.

Traditional test automation can execute scripts, but it struggles to explain failures, adapt safely to application changes, evaluate AI-powered features, or govern autonomous testing agents. AI-Native Software Testing shows practitioners how to design a modern testing architecture that combines Playwright, AI agents, LLMs, controlled self-healing, and governed CI/CD automation.

Deliver What Matters, When It Matters is a practical guide to delivery optimization for teams working in complex environments. Through real-world stories and actionable tools, it helps coaches, product managers, and delivery leaders close the gap between effort and impact.

What You Will LearnBy the end of this book, you will be able to:1.     Understand the core concepts of unsupervised learning and how it differs from supervised learning.2.     Preprocess and prepare datasets for clustering, including scaling, normalization, and handling outliers.3.     Implement popular clustering algorithms in Python, tuning parameters for optimal results.4.     Evaluate clustering performance using both internal and external metrics.5.     Apply clustering techniques to real-world problems such as customer segmentation, anomaly detection, and image grouping.6.     Work with high-dimensional data and understand techniques to reduce dimensionality while preserving patterns.7.     Use advanced clustering techniques to solve complex data grouping problems in large datasets.8.     Develop ethical awareness of privacy, bias, and fairness in AI applications. Benefits After Studying This Book For Students ·        Gain strong theoretical foundations in machine learning without supervision.·        Prepare for academic exams, assignments, and competitive exams like UGC NET, GATE, and data science interviews.·        Build portfolio-worthy projects to showcase in internships or job applications. For Job Seekers and Professionals ·        Learn industry-relevant clustering algorithms used in AI, marketing, healthcare, and cybersecurity.·        Enhance data analysis and problem-solving skills to stand out in interviews for roles such as Data Scientist, Machine Learning Engineer, or Business Analyst.·        Understand how to integrate clustering techniques into business solutions for better decision-making. For Researchers and Innovators ·        Explore cutting-edge clustering methods and hybrid models for high-dimensional and big data scenarios.·        Gain insights into current trends and future research opportunities in unsupervised learning.·        Leverage clustering techniques for research publications, AI prototypes, and academic projects.

Model Predictive Control sounds complicated—until you see how naturally it fits the way you already think. Look ahead. Plan. Adjust. Repeat. This book turns a powerful control method into something intuitive, practical, and surprisingly simple.

Secure boot is what separates a trusted device from a compromised one — but the chain of trust from hardware fuses to a verified OS is rarely explained clearly. This illustrated guide walks you through every layer: root of trust, key provisioning, bootloader handoffs, certificate chains, and real-world attack vectors. 8 chapters, all visual, zero fluff.

It is estimated that the number of IoT components will reach 12 trillion in 2030, which will probably generate a fourth Industrial Revolution, already called Industry 4.0. Esp32, the new star in the IoT arena, allows the fast and independent qualification of those who already have some classical IT knowledge and want to be part of this process.  

Learn how to create a real-world Continuous Delivery pipeline for a Spring Boot app by setting up a Kubernetes cluster and running Jenkins Pipelines in a scalable fashion (dynamically allocating Jenkins slaves as Kubernetes pods) to test, build, release and deploy a new version to testing, staging and production environments using Canary Release

This book aims to explain the concepts of Domain-driven Design in a way that it is easily applicable in practice. Each chapter contains a theoretical part which is explained from the point of view of practical applicability and then exercises with solutions based on a comprehensive, complex case study (real estate loans).