YARN Essentials. A comprehensive, hands-on guide to install, administer, and configure settings in YARN

Amol Fasale, Nirmal Kumar

Hands-On Artificial Intelligence for Cybersecurity. Implement smart AI systems for preventing cyber attacks and detecting threats and network anomalies

Alessandro Parisi

Today's organizations spend billions of dollars globally on cybersecurity. Artificial intelligence has emerged as a great solution for building smarter and safer security systems that allow you to predict and detect suspicious network activity, such as phishing or unauthorized intrusions.This cybersecurity book presents and demonstrates popular and successful AI approaches and models that you can adapt to detect potential attacks and protect your corporate systems. You'll learn about the role of machine learning and neural networks, as well as deep learning in cybersecurity, and you'll also learn how you can infuse AI capabilities into building smart defensive mechanisms. As you advance, you'll be able to apply these strategies across a variety of applications, including spam filters, network intrusion detection, botnet detection, and secure authentication.By the end of this book, you'll be ready to develop intelligent systems that can detect unusual and suspicious patterns and attacks, thereby developing strong network security defenses using AI.

Domain-Driven Refactoring. A hands-on DDD guide to transforming monoliths into modular systems and microservices

Alessandro Colla, Alberto Acerbis, Xin Yao

As software development continues to grow, mastering domain-driven design (DDD) will help transform your approach to complex systems. Filled with actionable insights and practical examples, this book is your essential guide to implementing DDD principles, covering its key concepts and practical applications in modern architecture.Alessandro, an eCommerce specialist and DDD expert with 30 years of experience, and Alberto, a dedicated backend developer, tap into their extensive expertise to help you refactor your monolith into a modular structure, whether it be evolving into microservices or enhancing a maintainable monolith, resulting in a system that adapts to changing business needs and non-functional requirements.You’ll explore vital DDD patterns like strategic design with bounded contexts and ubiquitous language, improving communication between technical and domain experts. The chapters take you through modeling techniques to manage complexity and increase flexibility, while also addressing microservices integration, including inter-service communication, transaction management, and data strategies.By the end of this book, you’ll be able to decompose a monolith and refine its architecture for adaptability, all while ensuring business logic remains central to your software design and development.

Smart Internet of Things Projects. Discover how to build your own smart Internet of Things projects and bring a new degree of interconnectivity to your world

Agus Kurniawan

Internet of Things (IoT) is a groundbreaking technology that involves connecting numerous physical devices to the Internet and controlling them. Creating basic IoT projects is common, but imagine building smart IoT projects that can extract data from physical devices, thereby making decisions by themselves.Our book overcomes the challenge of analyzing data from physical devices and accomplishes all that your imagination can dream up by teaching you how to build smart IoT projects. Basic statistics and various applied algorithms in data science and machine learning are introduced to accelerate your knowledge of how to integrate a decision system into a physical device.This book contains IoT projects such as building a smart temperature controller, creating your own vision machine project, building an autonomous mobile robot car, controlling IoT projects through voice commands, building IoT applications utilizing cloud technology and data science, and many more. We will also leverage a small yet powerful IoT chip, Raspberry Pi with Arduino, in order to integrate a smart decision-making system in the IoT projects.

Implementing Multifactor Authentication. Protect your applications from cyberattacks with the help of MFA

Marco Fanti

MFA has emerged as an essential defense strategy in the wide-ranging landscape of cybersecurity. This book is a comprehensive manual that assists you in picking, implementing, and resolving issues with various authentication products that support MFA. It will guide you to bolster application security without sacrificing the user experience.You'll start with the fundamentals of authentication and the significance of MFA to familiarize yourself with how MFA works and the various types of solutions currently available. As you progress through the chapters, you'll learn how to choose the proper MFA setup to provide the right combination of security and user experience. The book then takes you through methods hackers use to bypass MFA and measures to safeguard your applications. After familiarizing yourself with enabling and managing leading cloud and on-premise MFA solutions, you’ll see how MFA efficiently curbs cyber threats, aided by insights from industry best practices and lessons from real-world experiences. Finally, you’ll explore the significance of innovative advancements in this domain, including behavioral biometrics and passkeys.By the end of the book, you'll have the knowledge to secure your workforce and customers, empowering your organization to combat authentication fraud.

Extending Power BI with Python and R. Perform advanced analysis using the power of analytical languages - Second Edition

Luca Zavarella

With this updated second edition, you'll not only learn how to configure the Power BI environment to run Python and R scripts at peak performance—you'll also become familiar with the appropriate solutions to the most common problems you may encounter. Extending Power BI with Python and R explores data ingestion and data transformation extensions before moving on to focus on data enrichment and data visualization. You'll learn how to ingest data larger than available memory, import data from external sources, and transform data using complex algorithms, as well as implementing personal data de-identification methods such as pseudonymization, anonymization, and masking in Power BI. You'll find out how to call external APIs to enrich your data much faster, and address I/O performance issues using Python and R. Next, you'll learn advanced Python and R techniques to perform in-depth analysis and extract valuable information using statistics and machine learning. You'll also get to grips with the key statistical features of data sets by plotting multiple visual graphs in the process of building a machine learning model. Your knowledge will be tested through questions and answers at the end of each chapter.By the end of this book, you’ll be able to enrich your Power BI data models and unlock valuable insights using Python and R.

Django 5 By Example. Build powerful and reliable Python web applications from scratch - Fifth Edition

Antonio Melé, Paolo Melchiorre

If you want to learn Django by doing, this book is for you.Django 5 By Example is the fifth edition of the best-selling franchise that helps you build real-world web apps. This book will walk you through planning and creation, solving common problems, and implementing best practices using a step-by-step approach.You’ll cover a wide range of web application development topics through four different projects: a blog application, a social website, an e-commerce application, and an e-learning platform. Pick up what’s new in Django 5 as you build end-to-end Python web apps, follow detailed project plans, and understand the hows and whys of Django.This is a practical and approachable book that will have you creating web apps quickly.

Data Science Projects with Python. A case study approach to successful data science projects using Python, pandas, and scikit-learn

Stephen Klosterman

Data Science Projects with Python is designed to give you practical guidance on industry-standard data analysis and machine learning tools, by applying them to realistic data problems. You will learn how to use pandas and Matplotlib to critically examine datasets with summary statistics and graphs, and extract the insights you seek to derive. You will build your knowledge as you prepare data using the scikit-learn package and feed it to machine learning algorithms such as regularized logistic regression and random forest. You’ll discover how to tune algorithms to provide the most accurate predictions on new and unseen data. As you progress, you’ll gain insights into the working and output of these algorithms, building your understanding of both the predictive capabilities of the models and why they make these predictions.By then end of this book, you will have the necessary skills to confidently use machine learning algorithms to perform detailed data analysis and extract meaningful insights from unstructured data.