Practical gRPC. Build highly-connected systems with a framework that can run on any platform

Joshua B. Humphries, David Konsumer, David Muto, Robert Ross, ...

While building systems that contain several components, you need a framework that is fast and has minimal network overhead. gRPC is one such open-source tool that is quickly becoming popular and gaining popularity with programmers.Practical gRPC introduces you to gRPC and explains how it compares and contrasts with similar technologies. You’ll be introduced to key technologies such as Protocol Buffers, and work your way up from basic gRPC usage, all the way through to its more advanced capabilities. You’ll learn the best practices for defining and evolving your gRPC APIs, and discover how different tools can be leveraged to get the most out of gRPC and even extend it.By the end of this book, you'll have all the information you need to get started building systems with gRPC.

Practical Guide to Applied Conformal Prediction in Python. Learn and apply the best uncertainty frameworks to your industry applications

Valery Manokhin, Agus Sudjianto

In the rapidly evolving landscape of machine learning, the ability to accurately quantify uncertainty is pivotal. Practical Guide to Applied Conformal Prediction in Python addresses this need by offering an in-depth exploration of Conformal Prediction, a cutting-edge framework set to revolutionize uncertainty management in various ML applications.Embark on a comprehensive journey through Conformal Prediction, exploring its fundamentals and practical applications in binary classification, regression, time series forecasting, imbalanced data, computer vision, and NLP. Each chapter delves into specific aspects, offering hands-on insights and best practices for enhancing prediction reliability. The book concludes with a focus on multi-class classification nuances, providing expert-level proficiency to seamlessly integrate Conformal Prediction into diverse industries. Practical examples in Python using real-world datasets reinforce intuitive explanations, ensuring you acquire a robust understanding of this modern framework for uncertainty quantification.This guide is a beacon for mastering Conformal Prediction in Python, providing a blend of theory and practical application. It serves as a comprehensive toolkit to enhance machine learning skills, catering to professionals from data scientists to ML engineers.

Practical Guide to Azure Cognitive Services. Leverage the power of Azure OpenAI to optimize operations, reduce costs, and deliver cutting-edge AI solutions

Chris Seferlis, Christopher Nellis, Andy Roberts

Azure Cognitive Services and OpenAI are a set of pre-built artificial intelligence (AI) solution APIs that can be leveraged from existing applications, allowing customers to take advantage of Microsoft’s award-winning Vision, Speech, Text, Decision, and GPT-4 AI capabilities.With Practical Guide to Azure Cognitive Services, you’ll work through industry-specific examples of implementations to get a head-start in your production journey. You’ll begin with an overview of the categorization of Azure Cognitive Services and the benefits of embracing AI solutions for practical business applications. After that, you’ll explore the benefits of using Azure Cognitive Services to optimize efficiency and improve predictive capabilities. Then, you’ll learn how to leverage Vision capabilities for quality control, Form Recognizer to streamline supply chain nuances, language understanding to improve customer service, and Cognitive Search for next-generation knowledge-mining solutions.By the end of this book, you’ll be able to implement various Cognitive Services solutions that will help you enhance efficiency, reduce costs, and improve the customer experience at your organization. You’ll also be well equipped to automate mundane tasks by reaping the full potential of OpenAI.

Practical Hardware Pentesting. A guide to attacking embedded systems and protecting them against the most common hardware attacks

Jean-Georges Valle

If you’re looking for hands-on introduction to pentesting that delivers, then Practical Hardware Pentesting is for you. This book will help you plan attacks, hack your embedded devices, and secure the hardware infrastructure.Throughout the book, you will see how a specific device works, explore the functional and security aspects, and learn how a system senses and communicates with the outside world. You’ll set up a lab from scratch and then gradually work towards an advanced hardware lab—but you’ll still be able to follow along with a basic setup. As you progress, you’ll get to grips with the global architecture of an embedded system and sniff on-board traffic, learn how to identify and formalize threats to the embedded system, and understand its relationship with its ecosystem. You’ll discover how to analyze your hardware and locate its possible system vulnerabilities before going on to explore firmware dumping, analysis, and exploitation. The reverse engineering chapter will get you thinking from an attacker point of view; you’ll understand how devices are attacked, how they are compromised, and how you can harden a device against the most common hardware attack vectors. By the end of this book, you will be well-versed with security best practices and understand how they can be implemented to secure your hardware.

Practical Hardware Pentesting. Learn attack and defense techniques for embedded systems in IoT and other devices - Second Edition

Jean-Georges Valle

Practical Hardware Pentesting, Second Edition, is an example-driven guide that will help you plan attacks, hack your embedded devices, and secure the hardware infrastructure.Throughout the book, you’ll explore the functional and security aspects of a device and learn how a system senses and communicates with the outside world. You’ll set up a lab from scratch and gradually work towards an advanced hardware lab.The first part of this book will get you attacking the software of an embedded device. This will get you thinking from an attacker point of view; you’ll understand how devices are attacked, compromised, and how you can harden a device against the most common hardware attack vectors. As you progress, you’ll get to grips with the global architecture of an embedded system and sniff on-board traffic, learn how to identify and formalize threats to the embedded system, and understand its relationship with its ecosystem. This 2nd Edition covers real-world examples featuring various devices like smart TVs, baby monitors, or pacemakers, you’ll discover how to analyze hardware and locate its possible vulnerabilities before going on to explore firmware dumping, analysis, and exploitation.By the end of this book, you’ll and understand how to implement best practices to secure your hardware.

Practical HTML and CSS. Elevate your internet presence by creating modern and high-performance websites for the web - Second Edition

Brett Jephson, Lewis Coulson, Ana Carolina Silveira

In the ever-evolving landscape of web development, mastering HTML and CSS is crucial for building modern, responsive websites. This comprehensive guide equips you with the essential knowledge and skills you need to excel in web design and development.Starting with the foundational principles of HTML and CSS, the book swiftly advances to cover more complex topics, providing a thorough understanding of these vital technologies. You’ll learn how to build websites from scratch, create intuitive user input forms, and enhance web design by integrating multimedia elements like videos, animations, and themes. Emphasizing responsive web design principles, this book teaches you how to create layouts that flawlessly adapt to different devices using media queries. You’ll also get to grips with SEO essentials to optimize website visibility and search engine rankings. A dedicated section guides you through performance optimization techniques to ensure your websites deliver a smooth and lightning-fast user experience.By the end of this HTML and CSS book, you’ll have developed confidence in your web development skills, and you'll be well-equipped to build modern, visually appealing, and high-performing websites.

Practical Industrial Internet of Things Security. A practitioner's guide to securing connected industries

Sravani Bhattacharjee

Securing connected industries and autonomous systems is of primary concern to the Industrial Internet of Things (IIoT) community. Unlike cybersecurity, cyber-physical security directly ties to system reliability as well as human and environmental safety.This hands-on guide begins by establishing the foundational concepts of IIoT security with the help of real-world case studies, threat models, and reference architectures. You’ll work with practical tools to design risk-based security controls for industrial use cases and gain practical knowledge of multi-layered defense techniques, including identity and access management (IAM), endpoint security, and communication infrastructure. You’ll also understand how to secure IIoT lifecycle processes, standardization, and governance. In the concluding chapters, you’ll explore the design and implementation of resilient connected systems with emerging technologies such as blockchain, artificial intelligence, and machine learning.By the end of this book, you’ll be equipped with the all the knowledge required to design industry-standard IoT systems confidently.

Practical Internet of Things Security. Beat IoT security threats by strengthening your security strategy and posture against IoT vulnerabilities

Drew Van Duren, Brian Russell

With the advent of Internet of Things (IoT), businesses will be faced with defending against new types of threats. The business ecosystem now includes cloud computing infrastructure, mobile and fixed endpoints that open up new attack surfaces, a desire to share information with many stakeholders and a need to take action quickly based on large quantities of collected data. . It therefore becomes critical to ensure that cyber security threats are contained to a minimum when implementing new IoT services and solutions. . The interconnectivity of people, devices, and companies raises stakes to a new level as computing and action become even more mobile, everything becomes connected to the cloud, and infrastructure is strained to securely manage the billions of devices that will connect us all to the IoT. This book shows you how to implement cyber-security solutions, IoT design best practices and risk mitigation methodologies to address device and infrastructure threats to IoT solutions.This book will take readers on a journey that begins with understanding the IoT and how it can be applied in various industries, goes on to describe the security challenges associated with the IoT, and then provides a set of guidelines to architect and deploy a secure IoT in your Enterprise. The book will showcase how the IoT is implemented in early-adopting industries and describe how lessons can be learned and shared across diverse industries to support a secure IoT.

Practical Internet of Things Security. Design a security framework for an Internet connected ecosystem - Second Edition

Brian Russell, Drew Van Duren

With the advent of the Internet of Things (IoT), businesses have to defend against new types of threat. The business ecosystem now includes the cloud computing infrastructure, mobile and fixed endpoints that open up new attack surfaces. It therefore becomes critical to ensure that cybersecurity threats are contained to a minimum when implementing new IoT services and solutions.This book shows you how to implement cybersecurity solutions, IoT design best practices, and risk mitigation methodologies to address device and infrastructure threats to IoT solutions.In this second edition, you will go through some typical and unique vulnerabilities seen within various layers of the IoT technology stack and also learn new ways in which IT and physical threats interact. You will then explore the different engineering approaches a developer/manufacturer might take to securely design and deploy IoT devices. Furthermore, you will securely develop your own custom additions for an enterprise IoT implementation. You will also be provided with actionable guidance through setting up a cryptographic infrastructure for your IoT implementations. You will then be guided on the selection and configuration of Identity and Access Management solutions for an IoT implementation. In conclusion, you will explore cloud security architectures and security best practices for operating and managing cross-organizational, multi-domain IoT deployments.

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

Sunila Gollapudi

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.