React Projects. Build advanced cross-platform projects with React and React Native to become a professional developer - Second Edition

Roy Derks

Developed by Facebook, React is a popular library for building impressive user interfaces. React extends its capabilities to mobile platforms using the React Native framework and integrates with popular web and mobile tools to build scalable applications.React Projects is your guide to learning React development by using modern development patterns and integrating React with powerful web tools, such as GraphQL, Expo, and React 360. You'll start building a real-world project right from the first chapter and get hands-on with developing scalable applications as you advance to building more complex projects. Throughout the book, you'll use the latest versions of React and React Native to explore features such as routing, Context, and Hooks on multiple platforms, which will help you build full-stack web and mobile applications efficiently. Finally, you'll get to grips with unit testing with Jest and end-to-end testing with Cypress to build test-driven apps.By the end of this React book, you'll have developed the skills necessary to start building scalable React apps across web and mobile platforms.

Graph Machine Learning. Take graph data to the next level by applying machine learning techniques and algorithms

Claudio Stamile, Aldo Marzullo, Enrico Deusebio

Graph Machine Learning will introduce you to a set of tools used for processing network data and leveraging the power of the relation between entities that can be used for predictive, modeling, and analytics tasks. The first chapters will introduce you to graph theory and graph machine learning, as well as the scope of their potential use. You’ll then learn all you need to know about the main machine learning models for graph representation learning: their purpose, how they work, and how they can be implemented in a wide range of supervised and unsupervised learning applications. You'll build a complete machine learning pipeline, including data processing, model training, and prediction in order to exploit the full potential of graph data. After covering the basics, you’ll be taken through real-world scenarios such as extracting data from social networks, text analytics, and natural language processing (NLP) using graphs and financial transaction systems on graphs. You’ll also learn how to build and scale out data-driven applications for graph analytics to store, query, and process network information, and explore the latest trends on graphs. By the end of this machine learning book, you will have learned essential concepts of graph theory and all the algorithms and techniques used to build successful machine learning applications.

Learn AWS Serverless Computing. A beginner's guide to using AWS Lambda, Amazon API Gateway, and services from Amazon Web Services

Scott Patterson

Serverless computing is a way to run your code without having to provision or manage servers. Amazon Web Services provides serverless services that you can use to build and deploy cloud-native applications. Starting with the basics of AWS Lambda, this book takes you through combining Lambda with other services from AWS, such as Amazon API Gateway, Amazon DynamoDB, and Amazon Step Functions. You’ll learn how to write, run, and test Lambda functions using examples in Node.js, Java, Python, and C# before you move on to developing and deploying serverless APIs efficiently using the Serverless Framework. In the concluding chapters, you’ll discover tips and best practices for leveraging Serverless Framework to increase your development productivity. By the end of this book, you’ll have become well-versed in building, securing, and running serverless applications using Amazon API Gateway and AWS Lambda without having to manage any servers.

Linux Shell Scripting Essentials. Learn shell scripting to solve complex shell-related problems and to efficiently automate your day-to-day tasks

Sinny Kumari, Khem Raj

Instant MapReduce Patterns - Hadoop Essentials How-to. Practical recipes to write your own MapReduce solution patterns for Hadoop programs

Liyanapathirannahelage H Perera

MapReduce is a technology that enables users to process large datasets and Hadoop is an implementation of MapReduce. We are beginning to see more and more data becoming available, and this hides many insights that might hold key to success or failure. However, MapReduce has the ability to analyze this data and write code to process it.Instant MapReduce Patterns – Hadoop Essentials How-to is a concise introduction to Hadoop and programming with MapReduce. It is aimed to get you started and give you an overall feel for programming with Hadoop so that you will have a well-grounded foundation to understand and solve all of your MapReduce problems as needed.Instant MapReduce Patterns – Hadoop Essentials How-to will start with the configuration of Hadoop before moving on to writing simple examples and discussing MapReduce programming patterns.We will start simply by installing Hadoop and writing a word count program. After which, we will deal with the seven styles of MapReduce programs: analytics, set operations, cross correlation, search, graph, Joins, and clustering. For each case, you will learn the pattern and create a representative example program. The book also provides you with additional pointers to further enhance your Hadoop skills.

CISA - Certified Information Systems Auditor Study Guide. Achieve CISA certification with practical examples and over 850 exam-oriented practice questions - Second Edition

Hemang Doshi

With the latest updates and revised study material, this second edition of the Certified Information Systems Auditor Study Guide provides an excellent starting point for your CISA certification preparation. The book strengthens your grip on the core concepts through a three-step approach. First, it presents the fundamentals with easy-to-understand theoretical explanations. Next, it provides a list of key aspects that are crucial from the CISA exam perspective, ensuring you focus on important pointers for the exam. Finally, the book makes you an expert in specific topics by engaging you with self-assessment questions designed to align with the exam format, challenging you to apply your knowledge and sharpen your understanding.Moreover, the book comes with lifetime access to supplementary resources on an online platform, including CISA flashcards, practice questions, and valuable exam tips. With unlimited access to the website, you’ll have the flexibility to practice as many times as you desire, maximizing your exam readiness.By the end of this book, you’ll have developed the proficiency to successfully obtain the CISA certification and significantly upgrade your auditing career.

Malware Analysis Techniques. Tricks for the triage of adversarial software

Dylan Barker

Malicious software poses a threat to every enterprise globally. Its growth is costing businesses millions of dollars due to currency theft as a result of ransomware and lost productivity. With this book, you'll learn how to quickly triage, identify, attribute, and remediate threats using proven analysis techniques. Malware Analysis Techniques begins with an overview of the nature of malware, the current threat landscape, and its impact on businesses. Once you've covered the basics of malware, you'll move on to discover more about the technical nature of malicious software, including static characteristics and dynamic attack methods within the MITRE ATT&CK framework. You'll also find out how to perform practical malware analysis by applying all that you've learned to attribute the malware to a specific threat and weaponize the adversary's indicators of compromise (IOCs) and methodology against them to prevent them from attacking. Finally, you'll get to grips with common tooling utilized by professional malware analysts and understand the basics of reverse engineering with the NSA's Ghidra platform. By the end of this malware analysis book, you’ll be able to perform in-depth static and dynamic analysis and automate key tasks for improved defense against attacks.

Causal Inference and Discovery in Python. Unlock the secrets of modern causal machine learning with DoWhy, EconML, PyTorch and more

Aleksander Molak, Ajit Jaokar

Causal methods present unique challenges compared to traditional machine learning and statistics. Learning causality can be challenging, but it offers distinct advantages that elude a purely statistical mindset. Causal Inference and Discovery in Python helps you unlock the potential of causality.You’ll start with basic motivations behind causal thinking and a comprehensive introduction to Pearlian causal concepts, such as structural causal models, interventions, counterfactuals, and more. Each concept is accompanied by a theoretical explanation and a set of practical exercises with Python code. Next, you’ll dive into the world of causal effect estimation, consistently progressing towards modern machine learning methods. Step-by-step, you’ll discover Python causal ecosystem and harness the power of cutting-edge algorithms. You’ll further explore the mechanics of how “causes leave traces” and compare the main families of causal discovery algorithms. The final chapter gives you a broad outlook into the future of causal AI where we examine challenges and opportunities and provide you with a comprehensive list of resources to learn more.By the end of this book, you will be able to build your own models for causal inference and discovery using statistical and machine learning techniques as well as perform basic project assessment.