Rust Web Development with Rocket. A practical guide to starting your journey in Rust web development using the Rocket framework

Karuna Murti

Looking for a fast, powerful, and intuitive framework to build web applications? This Rust book will help you kickstart your web development journey and take your Rust programming skills to the next level as you uncover the power of Rocket - a fast, flexible, and fun framework powered by Rust.Rust Web Development with Rocket wastes no time in getting you up to speed with what Rust is and how to use it. You’ll discover what makes it so productive and reliable, eventually mastering all of the concepts you need to play with the Rocket framework while developing a wide set of web development skills. Throughout this book, you'll be able to walk through a hands-on project, covering everything that goes into making advanced web applications, and get to grips with the ins and outs of Rocket development, including error handling, Rust vectors, and wrappers. You'll also learn how to use synchronous and asynchronous programming to improve application performance and make processing user content easy.By the end of the book, you'll have answers to all your questions about creating a web application using the Rust language and the Rocket web framework.

Hands-On Computer Vision with TensorFlow 2. Leverage deep learning to create powerful image processing apps with TensorFlow 2.0 and Keras

Benjamin Planche, Eliot Andres

Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. This book will help you explore TensorFlow 2, the brand new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks.Hands-On Computer Vision with TensorFlow 2 starts with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the book demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts.By the end of the book, you will have both the theoretical understanding and practical skills to solve advanced computer vision problems with TensorFlow 2.0.

JIRA 6.x Administration Cookbook. Over 100 hands-on recipes to help you efficiently administer, customize, and extend your JIRA 6 implementation

Patrick Li

Software Architecture for Busy Developers. Talk and act like a software architect in one weekend

Stéphane Eyskens

Are you a seasoned developer who likes to add value to a project beyond just writing code? Have you realized that good development practices are not enough to make a project successful, and you now want to embrace the bigger picture in the IT landscape? If so, you're ready to become a software architect; someone who can deal with any IT stakeholder as well as add value to the numerous dimensions of software development.The sheer volume of content on software architecture can be overwhelming. However, Software Architecture for Busy Developers is here to help. Written by Stéphane Eyskens, author of The Azure Cloud Native Mapbook, this audiobook guides you through your software architecture journey in a pragmatic way using real-world scenarios. By drawing on over 20 years of consulting experience, Stéphane will help you understand the role of a software architect, without the fluff or unnecessarily complex theory.You'll begin by understanding what non-functional requirements mean and how they concretely impact target architecture. The audiobook then covers different frameworks used across the entire enterprise landscape with the help of use cases and examples. Finally, you'll discover ways in which the cloud is becoming a game changer in the world of software architecture.By the end of this audiobook, you'll have gained a holistic understanding of the architectural landscape, as well as more specific software architecture skills. You'll also be ready to pursue your software architecture journey on your own - and in just one weekend!

Before Machine Learning Volume 3 - Probability and Statistics for A.I . Master Probability, Statistics, and Their Role in AI's Future Evolution

Jorge Brasil

Delve into the importance of probability and statistics in AI, beginning with fundamental measures like mean, median, and variance. This book takes you on a journey through the basics of probability theory, introducing key concepts such as central tendency, variance, and probability distributions. It emphasizes the role of statistical measures in understanding and analyzing data.Building on these foundations, the book explores hypothesis testing, Bayesian inference, and statistical distributions in-depth. Readers will gain practical insights into essential techniques for model evaluation, maximum likelihood estimation, and the interpretation of data in the context of AI applications. Each concept is illustrated with practical examples and case studies to ensure clarity and application.Finally, advanced topics like Markov processes, hierarchical Bayesian models, and multivariate distributions are introduced. The book addresses critical areas like variance, correlation, and hypothesis testing, equipping readers with the skills to tackle real-world challenges in AI and machine learning. Whether you're a student, professional, or AI enthusiast, this book offers the essential statistical tools and knowledge to excel in the field.

JSF 1.2 Components. Develop advanced Ajax-enabled JSF applications

IAN HLAVATS

Today's web developers need powerful tools to deliver richer, faster, and smoother web experiences. JavaServer Faces includes powerful, feature-rich, Ajax-enabled UI components that provide all the functionality needed to build web applications in a Web 2.0 world. It's the perfect way to build rich, interactive, and Web 2.0-style Java web apps.This book provides a comprehensive introduction to the most popular JSF components available today and demonstrate step-by-step how to build increasingly sophisticated JSF user interfaces with standard JSF, Facelets, Apache Tomahawk/Trinidad, ICEfaces, JBoss Seam, JBoss RichFaces/Ajax4jsf, and JSF 2.0 components. JSF 1.2 Components is both an excellent starting point for new JSF developers, and a great reference and “how to” guide for experienced JSF professionals.This book progresses logically from an introduction to standard JSF HTML, and JSF Core components to advanced JSF UI development. As you move through the book, you will learn how to build composite views using Facelets tags, implement common web development tasks using Tomahawk components, and add Ajax capabilities to your JSF user interface with ICEfaces components. You will also learn how to solve the complex web application development challenges with the JBoss Seam framework. At the end of the book, you will be introduced to the new and up-coming JSF component libraries that will provide a road map of the future JSF technologies.

OpenGL Data Visualization Cookbook. Over 35 hands-on recipes to create impressive, stunning visuals for a wide range of real-time, interactive applications using OpenGL

William Lo, Raymond Chun Hing Lo

OpenGL is a great multi-platform, cross-language, and hardware-accelerated graphics interface for visualizing large 2D and 3D datasets. Data visualization has become increasingly challenging using conventional approaches as datasets become larger and larger, especially with the Big Data evolution. From a mobile device to a sophisticated high-performance computing cluster, OpenGL libraries provide developers with an easy-to-use interface to create stunning visuals in 3D in real time for a wide range of interactive applications.This book provides a series of easy-to-follow, hands-on tutorials to create appealing OpenGL-based visualization tools with minimal development time. We will first illustrate how to quickly set up the development environment in Windows, Mac OS X, and Linux. Next, we will demonstrate how to visualize data for a wide range of applications using OpenGL, starting from simple 2D datasets to increasingly complex 3D datasets with more advanced techniques. Each chapter addresses different visualization problems encountered in real life and introduces the relevant OpenGL features and libraries in a modular fashion.By the end of this book, you will be equipped with the essential skills to develop a wide range of impressive OpenGL-based applications for your unique data visualization needs, on platforms ranging from conventional computers to the latest mobile/wearable devices.

Before Machine Learning Volume 1 - Linear Algebra for A.I. The Fundamental Mathematics for Data Science and Artificial Intelligence

Jorge Brasil

In this book, you'll embark on a comprehensive journey through the fundamentals of linear algebra, a critical component for any aspiring machine learning expert. Starting with an introductory overview, the course explains why linear algebra is indispensable for machine learning, setting the stage for deeper exploration. You'll then dive into the concepts of vectors and matrices, understanding their definitions, properties, and practical applications in the field.As you progress, the course takes a closer look at matrix decomposition, breaking down complex matrices into simpler, more manageable forms. This section emphasizes the importance of decomposition techniques in simplifying computations and enhancing data analysis. The final chapter focuses on principal component analysis, a powerful technique for dimensionality reduction that is widely used in machine learning and data science. By the end of the course, you will have a solid grasp of how PCA can be applied to streamline data and improve model performance.This course is designed to provide technical professionals with a thorough understanding of linear algebra's role in machine learning. By the end, you'll be well-equipped with the knowledge and skills needed to apply linear algebra in practical machine learning scenarios.