TAGLINE Unlock Next-Level Scalable App Development with Monorepo and Bazel KEY FEATURES ● Unleash the transformative power of Monorepos with Bazel, revolutionizing your development workflow. ● Elevate your build system to unmatched levels of efficiency and reliability through comprehensive Bazel mastery. ● Propel yourself into the future of software development by mastering Bazel and harnessing the potential of Monorepo architecture. ● Optimize your builds for peak efficiency and unwavering reliability with expert insights and techniques in Bazel utilization. ● Unlock the gateway to scalable applications by leveraging the dynamic synergy of Bazel and Monorepo for unparalleled success. DESCRIPTION “Ultimate Scalable Monorepo Apps with Bazel" is the go-to guide for developers and engineers looking to maximize the potential of Bazel within a monorepo setup. It explores the intricacies of building large-scale applications, contrasting the monorepo approach with polyrepo setups and highlighting benefits like streamlined dependency management and improved collaboration. Through practical examples and real-world case studies, you'll learn how to harness Bazel's features for faster build times and consistent results across environments. Structured to cover all aspects of Bazel and monorepo development, from initial setup to advanced topics like custom rule creation and dependency management, this book provides actionable insights to enhance your development workflow. This guide equips you with the knowledge and skills to efficiently manage large codebases and contribute to more robust, scalable, and maintainable software projects. By the end, readers will be equipped to efficiently manage large codebases, leverage Bazel’s capabilities to speed up build and test processes, and ultimately, contribute to more robust, scalable, and maintainable software projects. WHAT WILL YOU LEARN ● Understand the fundamentals and importance of Bazel in modern development practices. ● Dive into the essentials of setting up and configuring Bazel for your projects. ● Explore the intricacies of defining build rules and optimizing configurations for efficient builds. ● Learn strategies for designing and executing scalable and comprehensive tests within a monorepo environment. ● Master effective dependency management techniques and version control practices. ● Discover techniques for streamlining your development workflow with Bazel integration. ● Analyze real-world case studies and examples to see Bazel in action and learn from practical scenarios. WHO IS THIS BOOK FOR? This book is tailored for software developers and architects who have a foundational understanding of software development principles and are looking to delve into the nuances of building large-scale applications using a monorepo structure and Bazel. Prior knowledge of basic version control concepts and familiarity with any programming language are essential for fully benefiting from this book. TABLE OF CONTENTS 1. Introduction 2. Getting Started with Bazel 3. Bazel Build Rules and Configuration 4. Testing Strategies in a monorepo 5. Dependency Management and Versioning 6. Hello-World Using Other Languages and Platforms 7. Streamlining Development Workflow 8. Structuring Monorepos for Success 9. Managing Large Codebases and Scale 10. Building and Deploying Services 11. Monitoring and Debugging Bazel 12. Advanced Bazel Concepts 13. Case Studies and Real-World Examples 14. Future Trends and Considerations APPENDIX A Bazel Cheat Sheet APPENDIX B Additional Resources Index

Discover Bazel, a new build and software test set of tools for today's programmers and developers. This book shows you how to speed up your builds and tests, and how to use Bazel in the context of your favorite programming language. You'll see that the languages and SDKs supported include Java, Android, iOS, and Go. What You Will LearnUse Bazel as a build toolTest software with Bazel Work with Java, C++, Android, iOS, Go, and other programming languagesRun Bazel on Linux, macOS, and WindowsScale and extend Bazel to other languages and platforms Who This Book Is For Experienced programmers looking for alternative build/test tools.

Take a deep dive into Kubernetes inner components and discover what really powers a Kubernetes cluster. This in-depth guide shines a light on Kubernetes' murky internals, to help you better plan cloud native architectures and ensure the reliability of your systems. To build and operate reliable Kubernetes-based systems, you need to understand what's going on below the surface. Core Kubernetes is an in-depth guide to Kubernetes' internal workings written by Kubernetes contributors Chris Love and Jay Vyas. It's packed with experience-driven insights and advanced techniques you won't find anywhere else. You'll understand the unique security concerns of container-based applications, minimize costly unused capacity, and get pro tips for maximizing performance. Diagrams, labs, and hands-on examples ensure that the complex ideas are easy to understand and practical to apply.

Bring magic to your mobile apps using TensorFlow Lite and Core ML Key FeaturesExplore machine learning using classification, analytics, and detection tasks.Work with image, text and video datasets to delve into real-world tasksBuild apps for Android and iOS using Caffe, Core ML and Tensorflow LiteBook Description Machine learning is a technique that focuses on developing computer programs that can be modified when exposed to new data. We can make use of it for our mobile applications and this book will show you how to do so. The book starts with the basics of machine learning concepts for mobile applications and how to get well equipped for further tasks. You will start by developing an app to classify age and gender using Core ML and Tensorflow Lite. You will explore neural style transfer and get familiar with how deep CNNs work. We will also take a closer look at Google’s ML Kit for the Firebase SDK for mobile applications. You will learn how to detect handwritten text on mobile. You will also learn how to create your own Snapchat filter by making use of facial attributes and OpenCV. You will learn how to train your own food classification model on your mobile; all of this will be done with the help of deep learning techniques. Lastly, you will build an image classifier on your mobile, compare its performance, and analyze the results on both mobile and cloud using TensorFlow Lite with an RCNN. By the end of this book, you will not only have mastered the concepts of machine learning but also learned how to resolve problems faced while building powerful apps on mobiles using TensorFlow Lite, Caffe2, and Core ML. What you will learnDemystify the machine learning landscape on mobileAge and gender detection using TensorFlow Lite and Core MLUse ML Kit for Firebase for in-text detection, face detection, and barcode scanningCreate a digit classifier using adversarial learningBuild a cross-platform application with face filters using OpenCVClassify food using deep CNNs and TensorFlow Lite on iOS Who this book is for Machine Learning Projects for Mobile Applications is for you if you are a data scientist, machine learning expert, deep learning, or AI enthusiast who fancies mastering machine learning and deep learning implementation with practical examples using TensorFlow Lite and CoreML. Basic knowledge of Python programming language would be an added advantage.

This book is the fifth volume in the successful book series Robot Operating System: The Complete Reference. The objective of the book is to provide the reader with comprehensive coverage on the Robot Operating System (ROS), which is currently considered to be the primary development framework for robotics applications, and the latest trends and contributing systems. The content is divided into six parts. Pat I presents for the first time the emerging ROS 2.0 framework, while Part II focuses on multi-robot systems, namely on SLAM and Swarm coordination. Part III provides two chapters on autonomous systems, namely self-driving cars and unmanned aerial systems. In turn, Part IV addresses the contributions of simulation frameworks for ROS. In Part V, two chapters explore robotic manipulators and legged robots. Finally, Part VI presents emerging topics in monocular SLAM and a chapter on fault tolerance systems for ROS. Given its scope, the book will offer a valuable companion for ROS users and developers, helping them deepen their knowledge of ROS capabilities and features.

Learn to build end-to-end AI apps from scratch for Android and iOS using TensorFlow Lite, CoreML, and PyTorch Key FeaturesBuild practical, real-world AI projects on Android and iOSImplement tasks such as recognizing handwritten digits, sentiment analysis, and moreExplore the core functions of machine learning, deep learning, and mobile visionBook Description We’re witnessing a revolution in Artificial Intelligence, thanks to breakthroughs in deep learning. Mobile Artificial Intelligence Projects empowers you to take part in this revolution by applying Artificial Intelligence (AI) techniques to design applications for natural language processing (NLP), robotics, and computer vision. This book teaches you to harness the power of AI in mobile applications along with learning the core functions of NLP, neural networks, deep learning, and mobile vision. It features a range of projects, covering tasks such as real-estate price prediction, recognizing hand-written digits, predicting car damage, and sentiment analysis. You will learn to utilize NLP and machine learning algorithms to make applications more predictive, proactive, and capable of making autonomous decisions with less human input. In the concluding chapters, you will work with popular libraries, such as TensorFlow Lite, CoreML, and PyTorch across Android and iOS platforms. By the end of this book, you will have developed exciting and more intuitive mobile applications that deliver a customized and more personalized experience to users. What you will learnExplore the concepts and fundamentals of AI, deep learning, and neural networksImplement use cases for machine vision and natural language processingBuild an ML model to predict car damage using TensorFlowDeploy TensorFlow on mobile to convert speech to textImplement GAN to recognize hand-written digitsDevelop end-to-end mobile applications that use AI principlesWork with popular libraries, such as TensorFlow Lite, CoreML, and PyTorchWho this book is for Mobile Artificial Intelligence Projects is for machine learning professionals, deep learning engineers, AI engineers, and software engineers who want to integrate AI technology into mobile-based platforms and applications. Sound knowledge of machine learning and experience with any programming language is all you need to get started with this book.

Take the next step in implementing various common and not-so-common neural networks with Tensorflow 1.x About This Book Skill up and implement tricky neural networks using Google's TensorFlow 1.x An easy-to-follow guide that lets you explore reinforcement learning, GANs, autoencoders, multilayer perceptrons and more. Hands-on recipes to work with Tensorflow on desktop, mobile, and cloud environment Who This Book Is For This book is intended for data analysts, data scientists, machine learning practitioners and deep learning enthusiasts who want to perform deep learning tasks on a regular basis and are looking for a handy guide they can refer to. People who are slightly familiar with neural networks, and now want to gain expertise in working with different types of neural networks and datasets, will find this book quite useful. What You Will Learn Install TensorFlow and use it for CPU and GPU operations Implement DNNs and apply them to solve different AI-driven problems. Leverage different data sets such as MNIST, CIFAR-10, and Youtube8m with TensorFlow and learn how to access and use them in your code. Use TensorBoard to understand neural network architectures, optimize the learning process, and peek inside the neural network black box. Use different regression techniques for prediction and classification problems Build single and multilayer perceptrons in TensorFlow Implement CNN and RNN in TensorFlow, and use it to solve real-world use cases. Learn how restricted Boltzmann Machines can be used to recommend movies. Understand the implementation of Autoencoders and deep belief networks, and use them for emotion detection. Master the different reinforcement learning methods to implement game playing agents. GANs and their implementation using TensorFlow. In Detail Deep neural networks (DNNs) have achieved a lot of success in the field of computer vision, speech recognition, and natural language processing. The entire world is filled with excitement about how deep networks are revolutionizing artificial intelligence. This exciting recipe-based guide will take you from the realm of DNN theory to implementing them practically to solve the real-life problems in artificial intelligence domain. In this book, you will learn how to efficiently use TensorFlow, Google's open source framework for deep learning. You will implement different deep learning networks such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Deep Q-learning Networks (DQNs), and Generative Adversarial Networks (GANs) with easy to follow independent recipes. You will learn how to make Keras as backend with TensorFlow. With a problem-solution approach, you will understand how to implement different deep neural architectures to carry out complex tasks at work. You will learn the performance of different DNNs on some popularly used data sets such as MNIST, CIFAR-10, Youtube8m, and more. You will not only learn about the different mobile and embedded platforms supported by TensorFlow but also how to set up cloud platforms for deep learning applications. Get a sneak peek of TPU architecture and how they will affect DNN future. By using crisp, no-nonsense recipes, you will become an expert in implementing deep learning techniques in growing real-world applications and research areas such as reinforcement learning, GANs, autoencoders and more. Style and approach This book consists of hands-on recipes where you'll deal with real-world problems. You'll execute a series of tasks as you walk through data mining challenges using TensorFlow 1.x. Your one-stop solution for common and not-so-common pain points, this is a book that you must have on the shelf.