Practical Internet of Things with JavaScript. Build standalone exciting IoT projects with Raspberry Pi 3 and JavaScript (ES5/ES6)

Arvind Ravulavaru

In this world of technology upgrades, IoT is currently leading with its promise to make the world a more smarter and efficient place.This book will show you how to build simple IoT solutions that will help you to understand how this technology works. We would not only explore the IoT solution stack, but we will also see how to do it with the world’s most misunderstood programming language - JavaScript. Using Raspberry Pi 3 and JavaScript (ES5/ES6) as the base to build all the projects, you will begin with learning about the fundamentals of IoT and then build a standard framework for developing all the applications covered in this book. You will then move on to build a weather station with temperature, humidity and moisture sensors and further integrate Alexa with it. Further, you will build a smart wearable for understanding the concept of fall detection. You will then extend it with the 'If This Then That' (IFTTT) rules engine to send an email on fall detection. Finally, you will be working with the Raspberry Pi 3 camera module and surveillance with a bit of facial detection using Amazon Rekognition platform.At the end of the book, you will not only be able to build standalone exciting IoT applications but also learn how you can extend your projects to another level.

Practical Linux Security Cookbook. Click here to enter text

Tajinder Kalsi

With the growing popularity of Linux, more and more administrators have started moving to the system to create networks or servers for any task. This also makes Linux the first choice for any attacker now. Due to the lack of information about security-related attacks, administrators now face issues in dealing with these attackers as quickly as possible. Learning about the different types of Linux security will help create a more secure Linux system.Whether you are new to Linux administration or experienced, this book will provide you with the skills to make systems more secure.With lots of step-by-step recipes, the book starts by introducing you to various threats to Linux systems. You then get to walk through customizing the Linux kernel and securing local files. Next you will move on to manage user authentication locally and remotely and also mitigate network attacks. Finally, you will learn to patch bash vulnerability and monitor system logs for security.With several screenshots in each example, the book will supply a great learning experience and help you create more secure Linux systems.

Practical Linux Security Cookbook. Secure your Linux environment from modern-day attacks with practical recipes - Second Edition

Tajinder Kalsi

Over the last few years, system security has gained a lot of momentum and software professionals are focusing heavily on it. Linux is often treated as a highly secure operating system. However, the reality is that Linux has its share of security ?aws, and these security ?aws allow attackers to get into your system and modify or even destroy your important data. But there’s no need to panic, since there are various mechanisms by which these ?aws can be removed, and this book will help you learn about different types of Linux security to create a more secure Linux system. With a step-by-step recipe approach, the book starts by introducing you to various threats to Linux systems. Then, this book will walk you through customizing the Linux kernel and securing local files. Next, you will move on to managing user authentication both locally and remotely and mitigating network attacks. Later, you will learn about application security and kernel vulnerabilities. You will also learn about patching Bash vulnerability, packet filtering, handling incidents, and monitoring system logs. Finally, you will learn about auditing using system services and performing vulnerability scanning on Linux.By the end of this book, you will be able to secure your Linux systems and create a robust environment.

Practical Machine Learning Cookbook. Supervised and unsupervised machine learning simplified

Atul Tripathi

Machine learning has become the new black. The challenge in today’s world is the explosion of data from existing legacy data and incoming new structured and unstructured data. The complexity of discovering, understanding, performing analysis, and predicting outcomes on the data using machine learning algorithms is a challenge. This cookbook will help solve everyday challenges you face as a data scientist. The application of various data science techniques and on multiple data sets based on real-world challenges you face will help you appreciate a variety of techniques used in various situations.The first half of the book provides recipes on fairly complex machine-learning systems, where you’ll learn to explore new areas of applications of machine learning and improve its efficiency. That includes recipes on classifications, neural networks, unsupervised and supervised learning, deep learning, reinforcement learning, and more.The second half of the book focuses on three different machine learning case studies, all based on real-world data, and offers solutions and solves specific machine-learning issues in each one.

Practical Machine Learning. Learn how to build Machine Learning applications to solve real-world data analysis challenges with this Machine Learning book – packed with practical tutorials

This book explores an extensive range of machine learning techniques uncovering hidden tricks and tips for several types of data using practical and real-world examples. While machine learning can be highly theoretical, this book offers a refreshing hands-on approach without losing sight of the underlying principles. Inside, a full exploration of the various algorithms gives you high-quality guidance so you can begin to see just how effective machine learning is at tackling contemporary challenges of big dataThis is the only book you need to implement a whole suite of open source tools, frameworks, and languages in machine learning. We will cover the leading data science languages, Python and R, and the underrated but powerful Julia, as well as a range of other big data platforms including Spark, Hadoop, and Mahout. Practical Machine Learning is an essential resource for the modern data scientists who want to get to grips with its real-world application.With this book, you will not only learn the fundamentals of machine learning but dive deep into the complexities of real world data before moving on to using Hadoop and its wider ecosystem of tools to process and manage your structured and unstructured data. You will explore different machine learning techniques for both supervised and unsupervised learning; from decision trees to Naïve Bayes classifiers and linear and clustering methods, you will learn strategies for a truly advanced approach to the statistical analysis of data. The book also explores the cutting-edge advancements in machine learning, with worked examples and guidance on deep learning and reinforcement learning, providing you with practical demonstrations and samples that help take the theory–and mystery–out of even the most advanced machine learning methodologies.

Practical Machine Learning on Databricks. Seamlessly transition ML models and MLOps on Databricks

Debu Sinha

Unleash the potential of databricks for end-to-end machine learning with this comprehensive guide, tailored for experienced data scientists and developers transitioning from DIY or other cloud platforms. Building on a strong foundation in Python, Practical Machine Learning on Databricks serves as your roadmap from development to production, covering all intermediary steps using the databricks platform. You’ll start with an overview of machine learning applications, databricks platform features, and MLflow. Next, you’ll dive into data preparation, model selection, and training essentials and discover the power of databricks feature store for precomputing feature tables. You’ll also learn to kickstart your projects using databricks AutoML and automate retraining and deployment through databricks workflows. By the end of this book, you’ll have mastered MLflow for experiment tracking, collaboration, and advanced use cases like model interpretability and governance. The book is enriched with hands-on example code at every step. While primarily focused on generally available features, the book equips you to easily adapt to future innovations in machine learning, databricks, and MLflow.

Practical Machine Learning with R. Define, build, and evaluate machine learning models for real-world applications

Brindha Priyadarshini Jeyaraman, Ludvig Renbo Olsen, Monicah Wambugu

With huge amounts of data being generated every moment, businesses need applications that apply complex mathematical calculations to data repeatedly and at speed. With machine learning techniques and R, you can easily develop these kinds of applications in an efficient way.Practical Machine Learning with R begins by helping you grasp the basics of machine learning methods, while also highlighting how and why they work. You will understand how to get these algorithms to work in practice, rather than focusing on mathematical derivations. As you progress from one chapter to another, you will gain hands-on experience of building a machine learning solution in R. Next, using R packages such as rpart, random forest, and multiple imputation by chained equations (MICE), you will learn to implement algorithms including neural net classifier, decision trees, and linear and non-linear regression. As you progress through the book, you’ll delve into various machine learning techniques for both supervised and unsupervised learning approaches. In addition to this, you’ll gain insights into partitioning the datasets and mechanisms to evaluate the results from each model and be able to compare them. By the end of this book, you will have gained expertise in solving your business problems, starting by forming a good problem statement, selecting the most appropriate model to solve your problem, and then ensuring that you do not overtrain it.

Practical Maya Programming with Python. Unleash the power of Python in Maya and unlock your creativity

Robert Galanakis

Practical Memory Forensics. Jumpstart effective forensic analysis of volatile memory

Svetlana Ostrovskaya, Oleg Skulkin

Memory Forensics is a powerful analysis technique that can be used in different areas, from incident response to malware analysis. With memory forensics, you can not only gain key insights into the user's context but also look for unique traces of malware, in some cases, to piece together the puzzle of a sophisticated targeted attack.Starting with an introduction to memory forensics, this book will gradually take you through more modern concepts of hunting and investigating advanced malware using free tools and memory analysis frameworks. This book takes a practical approach and uses memory images from real incidents to help you gain a better understanding of the subject and develop the skills required to investigate and respond to malware-related incidents and complex targeted attacks. You'll cover Windows, Linux, and macOS internals and explore techniques and tools to detect, investigate, and hunt threats using memory forensics. Equipped with this knowledge, you'll be able to create and analyze memory dumps on your own, examine user activity, detect traces of fileless and memory-based malware, and reconstruct the actions taken by threat actors.By the end of this book, you'll be well-versed in memory forensics and have gained hands-on experience of using various tools associated with it.

Practical Microservices with Dapr and .NET. A developer's guide to building cloud-native applications using the Dapr event-driven runtime

Davide Bedin, Mark Russinovich

Over the last decade, there has been a huge shift from heavily coded monolithic applications to finer, self-contained microservices. Dapr is a new, open source project by Microsoft that provides proven techniques and best practices for developing modern applications. It offers platform-agnostic features for running your applications on public cloud, on-premises, and even on edge devices.This book will help you get to grips with microservice architectures and how to manage application complexities with Dapr in no time. You'll understand how Dapr offers ease of implementation while allowing you to work with multiple languages and platforms. You'll also understand how Dapr's runtime, services, building blocks, and software development kits (SDKs) help you to simplify the creation of resilient and portable microservices. Dapr provides an event-driven runtime that supports the essential features you need to build microservices, including service invocation, state management, and publish/subscribe messaging. You'll explore all of those in addition to various other advanced features with this practical guide to learning Dapr.By the end of this book, you'll be able to write microservices easily using your choice of language or framework by implementing industry best practices to solve problems related to distributed systems.

Practical Microservices with Dapr and .NET. A developer's guide to building cloud-native applications using the event-driven runtime - Second Edition

Davide Bedin, Mark Russinovich

This second edition will help you get to grips with microservice architectures and how to manage application complexities with Dapr in no time. You'll understand how Dapr simplifies development while allowing you to work with multiple languages and platforms. Following a C# sample, you'll understand how Dapr's runtime, building blocks, and software development kits (SDKs) help you to simplify the creation of resilient and portable microservices.Dapr provides an event-driven runtime that supports the essential features you need for building microservices, including service invocation, state management, and publish/subscribe messaging. You'll explore all of those in addition to various other advanced features with this practical guide to learning Dapr. With a focus on deploying the Dapr sample application to an Azure Kubernetes Service cluster and to the Azure Container Apps serverless platform, you’ll see how to expose the Dapr application with NGINX, YARP, and Azure API Management.By the end of this book, you'll be able to write microservices easily by implementing industry best practices to solve problems related to distributed systems.

Practical Mobile Forensics. A hands-on guide to mastering mobile forensics for the iOS, Android, and the Windows Phone platforms - Second Edition

Heather Mahalik, Rohit Tamma, Satish Bommisetty

Mobile phone forensics is the science of retrieving data from a mobile phone under forensically sound conditions. This book is an update to Practical Mobile Forensics and it delves into the concepts of mobile forensics and its importance in today's world. We will deep dive into mobile forensics techniques in iOS 8 - 9.2, Android 4.4 - 6, and Windows Phone devices. We will demonstrate the latest open source and commercial mobile forensics tools, enabling you to analyze and retrieve data effectively. You will learn how to introspect and retrieve data from cloud, and document and prepare reports for your investigations.By the end of this book, you will have mastered the current operating systems and techniques so you can recover data from mobile devices by leveraging open source solutions.

Practical Mobile Forensics. A hands-on guide to mastering mobile forensics for the iOS, Android, and the Windows Phone platforms - Third Edition

Rohit Tamma, Oleg Skulkin, Heather Mahalik, Satish Bommisetty

Covering up-to-date mobile platforms, this book will focuses on teaching you the most recent techniques for investigating mobile devices. We delve mobile forensics techniques in iOS 9-11, Android 7-8 devices, and Windows 10. We will demonstrate the latest open source and commercial mobile forensics tools, enabling you to analyze and retrieve data effectively. You will learn how to introspect and retrieve data from the cloud, and document and prepare reports of your investigations. By the end of this book, you will have mastered the current operating systems and the relevant techniques to recover data from mobile devices by leveraging open source solutions.

Practical Mobile Forensics. Dive into mobile forensics on iOS, Android, Windows, and BlackBerry devices with this action-packed, practical guide

Satish Bommisetty, Rohit Tamma, Heather Mahalik

Practical Mobile Forensics. Forensically investigate and analyze iOS, Android, and Windows 10 devices - Fourth Edition

Rohit Tamma, Oleg Skulkin, Heather Mahalik, Satish Bommisetty

Mobile phone forensics is the science of retrieving data from a mobile phone under forensically sound conditions. This updated fourth edition of Practical Mobile Forensics delves into the concepts of mobile forensics and its importance in today's world.The book focuses on teaching you the latest forensic techniques to investigate mobile devices across various mobile platforms. You will learn forensic techniques for multiple OS versions, including iOS 11 to iOS 13, Android 8 to Android 10, and Windows 10. The book then takes you through the latest open source and commercial mobile forensic tools, enabling you to analyze and retrieve data effectively. From inspecting the device and retrieving data from the cloud, through to successfully documenting reports of your investigations, you'll explore new techniques while building on your practical knowledge. Toward the end, you will understand the reverse engineering of applications and ways to identify malware. Finally, the book guides you through parsing popular third-party applications, including Facebook and WhatsApp.By the end of this book, you will be proficient in various mobile forensic techniques to analyze and extract data from mobile devices with the help of open source solutions.

Practical Model-Driven Enterprise Architecture. Design a mature enterprise architecture repository using Sparx Systems Enterprise Architect and ArchiMate® 3.1

Mudar Bahri, Joe Williams

Most organizations face challenges in defining and achieving evolved enterprise architecture practices, which can be a very lengthy process even if implemented correctly. Developers, for example, can build better solutions only if they receive the necessary design information from architects, and decision-makers can make appropriate changes within the organization only if they know the implications of doing so.The book starts by addressing the problems faced by enterprise architecture practitioners and provides solutions based on an agile approach to enterprise architecture, using ArchiMate® 3.1 as an industry standard and Sparx EA as the modeling tool. You'll learn with the help of a fictional organization that has three business units, each expecting something different from you as the enterprise architect. You'll build the practice, satisfy the different requirements of each business unit, and share the knowledge with others so they can follow your steps. Toward the end, you'll learn how to put the diagrams and the content that you have developed into documents, presentations, and web pages that can be published and shared with any stakeholder.By the end of this book, you'll be able to build a functional enterprise architecture practice that supports every part of your organization. You'll also have developed the necessary skills to populate your enterprise architecture repository with references and artifacts.