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Linux BIBLE (10th ed.)

The rest of this book provides you with hands-on activities to help you gain that expertise. Finally, I show you how to apply that expertise to cloud technologies, including automation tools, such as Ansible, and containerization orchestration technologies, such as Kubernetes and OpenShift.

Linux for Networking Professionals

This book is meant for anyone tasked with administering network infrastructure of almost any kind. If you are interested in the nuts and bolts of how things work in your network, this book is for you! You'll also find our discussion interesting if you are often left wondering how you will deliver the various services on your network that your organization needs, but might not have the budget to pay for commercial products. We'll cover how each of the Linux services we discuss works, as well as how you might configure them in a typical environment.

Graph-Powered Machine Learning

This book took more than three years to be released. It required a lot of work—definitely more than what I thought when this crazy idea hit my mind. At the same time, it has been the most exciting experience of my career up until now. (And, yes, I am planning a second book.) I enjoyed crafting this book, but it was a long journey. That’s why I’d like to thank quite a few people for helping me along the way

Hands-on Application Development using Spring Boot

This book will guide you on how to make the best use of the strength that Spring Boot provides. You’ll gain an understanding of how Spring Boot configuration works in conjunction with application development, including auto-configuration and overriding default configurations. You will learn to develop scalable, dependable microservices to accelerate the development lifecycle of a cloud-based application. Each chapter will walk you through the features of Spring Boot as a Software Development Framework, such as performing Create, Read, Update, and Delete (CRUD) operations on a database and securing web services with appropriate logging.

Inside Deep Learning Math, Algorithms, Models

This book is a compilation of my knowledge in deep learning. It covers all the key topics I would like to be understood by an ideal candidate I would hire. These include a breadth of topic areas so you can begin to recognize and reuse patterns, positioning you to be effective in any area. It is critical to me that the book provides more than rote “use this model for this kind of problem” instruction. This book delves into why and how different models are selected. Hopefully, once you have finished reading this book,you will understand how the interplay between math, code, and intuition is built and grown, so you will be equipped to keep abreast of new developments in the field.

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.

Biologiya va genetika

Qo'llanmadan biologiya faniga, genetikaga qiziquvchi oquvchilar, oliy o'quv yurtiga kirish imtihonlariga hozirlanayotgan abituriyentlar hamda o'qituvchilar foydalanishlari mumkin.

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