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Deep Belief Nets in C++ and CUDA C: V.1
This book is intended primarily for readers who already have at least a basic knowledge of neural networks but are interested in learning about, experimenting with, and perhaps even programming deep belief nets. The salient features of this book are the following: The book provides motivation for the deep belief net paradigm. It presents the most important equations for the most common deep belief net components and justifies them to a modest degree.
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Practical System Programming with C
Linux is an open source, Unix-like operating system based on the Linux kernel. It was developed by Linus Torvalds in 1991. It is used in personal computers, mainframe computers, supercomputers, Android mobile devices, routers, and embedded systems. Linux is a very lightweight and powerful kernel that effectively communicates with software programs through any kind of hardware.
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Deep Learning at Scale
I started my professional career as a software engineer. Over the course of my time in that role, I became deeply interested and involved in running software and systems at scale. I learned a lot about distributed systems, performance, optimizations, and run‐ ning them reliably at scale.
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Ҳуқуқ фалсафаси
Ушбу қисқача ўқув қўлланмаси ҳуқуқ фалсафасига багишланган. Китобда ҳуқуқ фалсафасининг умумий муаммолари, шунингдек ҳуқуқ фалсафаси умумжаҳон тарихининг асосий босқичлари, йуналишлари ва тамойиллари ҳамда XX асрда чет эл ҳуқуқ фалсафасининг ривожланиши алоҳида мустақил илмий ва ўқув фани сифатида ёритилган.
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.NET MAUI Cross-Platform Application Development (Second Ed.)
.NET MAUI is a cross-platform technology developed by Microsoft. The inaugural edition of this book was authored using .NET 6. However, this second edition coincides with the diverse improvements initiated with the release of .NET 8. The latest .NET MAUI release predominantly seeks to enhance code quality. Simultaneously, updates have been made to the development environment that supports iOS and Android, upgrading to Xcode 15 and Android API 34 respectively.
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Problem Solving in Data Structures & Algorithms Using C# (First Ed.)
interview. It is highly recommended that the user should read the problem statement first, then he should try to solve the problems by himself and then only he should look into the solution to find the approach of the book. Practicing more and more problems will increase your thinking capacity and you will be able to handle new problems in an interview. System design is a topic that is not asked much from a fresher from college, but as you gain experience its importance increase.
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Understanding the LINUX KERNEL
In the spring semester of 1997, we taught a course on operating systems based on Linux 2.0. The idea was to encourage students to read the source code. To achieve this, we assigned term projects consisting of making changes to the kernel and performing tests on the modified version. We also wrote course notes for our students about a few critical features of Linux such as task switching and task scheduling.
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Practical Artificial Intelligence
Practical Artificial Intelligence (PAI) is a book that proposes a new model for learning. Most AI books deeply focus on theory and abandon practical problems that demonstrate the theory introduced throughout the book.
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Spring Security in Action (Second Ed.)
The journey through software development is an enthralling dance of building, learning, teaching, and often, unlearning. Ever since I began my journey in 2007, I’ve found myself gracefully expanding my role from being solely a developer to being a developer and trainer. While both roles have their unique charm, it’s the art of imparting knowledge, nurturing curiosity, and witnessing the aha moments of fellow learners that truly lights a fire in me. But let’s face it, the realms of development and training are deeply intertwined. To be a torchbearer, illuminating the way for others, one must first have their feet firmly rooted in the constantly evolving terrains of software application.
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Think Like a Data Scientist
In 2012, an article in the Harvard Business Review named the role of data scientist “the sexiest job of the 21st century.” With 87 years left in the century, it’s fair to say they might yet change their minds. Nevertheless, at the moment, data scientists are getting a lot of attention, and as a result, books about data science are proliferating. There would be no sense in adding another book to the pile if it merely repeated or repackaged text that is easily found elsewhere. But, while surveying new data science literature, it became clear to me that most authors would rather explain how to use all the latest tools and technologies than discuss the nuanced problem-solving nature of the data science process.
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Web Application Security (Second Ed.)
Welcome to Web Application Security: Exploitation and Countermeasures for Modern Web Applications. In this preface, we will discuss the book’s content and who this book is for, including the skill sets required to make the most of the technical content in the following chapters. Reading the preface will help you understand if this book is for you.
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Voice Applications for Alexa and Google Assistant
many Google products day-to-day. My music provider of choice is Google Play Music, my wife and I chat during the day on Hangouts, I use Google Calendar, and more. My interest was strong enough that I flew to the United States just to pick up a device. (Well,that and to see my then girlfriend, now wife, who was still living in Brooklyn.) Of course I was going to start building Actions for the Assistant, too.
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The Art of Randomness
Even though the ancient civilizations understood randomness (and philosophized about its role in the universe, causality, and free will), they did not possess the understanding of probabilistic behavior and long-term frequencies. In fact, it wasn’t until the Renaissance that scientists started treating chance with rigor.
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Probabilistic Deep Learning
All three of us, the authors, have a background in statistics. We started our journey in DL together in 2014. We got so excited about it that DL is still in the center of our professional lives. DL has a broad range of applications, but we are especially fascinated by the power of combining DL models with probabilistic approaches as used in statistics. In our experience, a deep understanding of the potential of probabilistic DL requires both insight into the underlying methods and practical experience. Therefore, we tried to find a good balance of both ingredients in this book.
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Writing a C Compiler
When we talk about how programming languages work, we tend to borrow metaphors from fantasy novels: compilers are magic, and the people who work on them are wizards. Dragons may be involved somehow. But in the day-to-day lives of most programmers, compilers behave less like magical artifacts and more like those universal translator earpieces from science fiction.
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Deep Reinforcement Learning in Unity
Machine learning has been instrumental in shaping the scope of technology since its inception. ML has played an important role in the development of things such as autonomous vehicles and robotics. Deep reinforcement learning is that field of learning where agents learn with help of rewards—a thought which has been derived from nature. Through this book, the author tries to present the diversity of reinforcement learning algorithms in game development as well as in scientific research.