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Machine Learning With Applications In Information Security

For the past several years, I’ve been teaching a class on “Topics in Information Security.” Each time I taught this course, I’d sneak in a few more machine learning topics. For the past couple of years, the class has been turned on its head, with machine learning being the focus, and information security only making its appearance in the applications. Unable to find a suitable textbook, I wrote a manuscript, which slowly evolved into this book.

Linux Device Driver Development

This book will begin with two chapters that will help you understand the basics of drivers and prepare you for the long journey through the Linux kernel. This book will then cover driver development based on Linux subsystems, such as memory management, industrial input/output (IIO), general-purpose input/output (GPIO), interrupt request (IRQ) management, and Inter-Integrated Circuit (I2C) and Serial Peripheral Interface (SPI). The book will also cover a practical approach to direct memory access and register map abstraction.

Machine Learning Engineering in Action

This book doesn’t aim to be a guide to applied ML. We’re not going to be covering algorithms or theories on why one model is better than another for a particular use case, nor will we delve into all the details to solve individual problems. Rather, this book is a guide to avoid the pitfalls that I’ve seen so many teams fall into (and ones that I’ve had to claw my way out of as a practitioner). It is a generalized approach to using DS techniques to solve problems in a way that you, your customers (the internal ones at your company), and your peers will not regret. It’s a guide to help you avoid making some of the really stupid mistakes that I’ve made.

Mastering API Architecture Defining, Connecting, and Securing Distributed Systems and Microservices

This book has been designed to provide a complete picture on designing,building, operating and evolving an API Architecture. We will share through both writing and case study key focus areas for consideration for getting the best architectural results building an API architecture.

Beginning Git and GitHub

This book has a clear objective: to serve as the resource I wish I had when I started my tech career. Each chapter is designed to teach you only what you need to know as a beginner. It’s not an exhaustive reference book, but it will equip you with the necessary knowledge to significantly impact your career.

Mastering C++ Programming Language

C++ is a programming language that gives programs a reasonable construction and works with code reuse, reducing improvement costs. C++ is a convenient programming language that might be utilized to make applications that sudden spike in demand for various frameworks. C++ is fun and primary language to learn.

Beginning jOOQ

This book isn’t about the fundamentals of SQL. Or even the joys of SQL per se (there are many). This book is about taking a different look at handling SQL work in Java.

Beginning Mathematica and Wolfram for Data Science

Why is data science important nowadays? Data science is an active topic that is evolving daily; new methods, techniques, and data are created daily. Data science is an interdisciplinary field involving scientific methods, algorithms, and systematic procedures to extract data sets and thus better understand the data in its different structures. It is a continuation of some theoretical data analysis fields such as statistics, data mining, machine learning, and pattern analysis. With a unique objective, to extract quantitative and qualitative information of value from the data being recollected from various sources, and thus be able to objectively count an event for decision-making, product development, pattern detection, or identification of new business areas.

Beginning Spring Boot 3

Spring is the most popular Java-based framework for building enterprise applications. The Spring Framework provides a rich ecosystem of projects to address modern application needs, like security, simplified access to relational and NoSQL datastores, batch processing, integration with social networking sites, and large volumes of data streams processing. As Spring is a very flexible and customizable framework, there are usually multiple ways to configure an application. Although it is a good thing to have multiple options, it can be overwhelming for beginners. Spring Boot addresses this “Spring applications need complex configuration” problem by using its powerful autoconfiguration mechanism.

Modern Microservices With Spring Boot 3 And Spring Cloud

Microservices, also known as the microservice architecture,is an architectural style that structures an application as a collection of loosely coupled services. These services are fine-grained and the protocols are lightweight. The main goal of microservices is to accelerate software development by enabling continuous delivery and deployment of large,complex applications. Let's delve into the key characteristics and principles of microservices

Blazor WebAssembly By Example

Hi, friends! I love a good second edition. It’s an opportunity to update and add to something that’s already great. You take feedback from the readers and the community, absorb the zeitgeist, and turn an A into an A+. Toi has taken Blazor WebAssembly By Example to the next level and now we welcome you all, readers old and new. I have known Toi Wright for more than 17 years. I first met her at the Microsoft MVP Summit in Redmond back in 2005, if you can believe that. She is a brilliant technologist, community leader, and tech organizer, and we see each other every year at the annual Microsoft MVP Summit. I’ve had the opportunity to travel from my home in Portland to beautiful Dallas to speak in person at the Dallas ASP.NET User Group where she’s the president and founder. Toi has been very active in the ASP.NET community for many years. She brings energy and expertise to everything she does. She has written courseware for Microsoft on ASP.NET and this is her third book on the topic. She’s a respected programmer, architect, and communicator.

.NET MAUI for C# Developers

This book is targeted at anyone who has a fundamental understanding of C# and wishes to write cross-platform applications. If you are not a C# programmer but have experience with another objectoriented program, you should have no trouble following the examples.

OpenShift in Action

We think this is important, because the ultimate goal of DevOps is to enable and enhance communication between developer and operations teams that historically have been placed in adversarial (at best) relationships. To accomplish this, the two authors each specialize in one of these roles. For us, writing this book has been an amazing learning experience in how DevOps can work for just about anything, including writing a book.

Build Your Own Programming Language

This book is structured to guide the reader through the nuanced process of developing a programming language. Beginning with motivations and types of language implementations, Jeffery sets the stage for understanding the fundamental “why” behind language design. He intricately discusses organizing a bytecode language and differentiates between programming languages and libraries, laying a solid foundation for both novices and experienced programmers.

Low-Level Programming

This book is primarily for those of you beginning your journey in the vast arena of learning and understanding modern Linux kernel architecture and internals, Linux kernel module development and, to some extent, Linux device driver development. It’s also very much targeted at those of you who have already been working on Linux modules and/or drivers, who wish to gain a much deeper, well-structured understanding of Linux kernel architecture, memory management, task scheduling, cgroups, and synchronization.

Low-Code AI

This book was created as a first step for those who wish to become ML practitioners, not as a book to turn you into an ML expert. We do not cover the theory of ML in detail, nor do we cover all of the topics from statistics and mathematics needed to be a successful data scientist. We cover the theory that is needed for the projects discussed in this book as a way to ease you into working on ML projects, but going farther than that would be beyond the scope here. We do, however, give many references to resources where you can dive deeper if you are interested in doing so.