A definitive guide to creating an intelligent web application with the best of machine learning and JavaScript About This Book ? Solve complex computational problems in browser with JavaScript ? Teach your browser how to learn from rules using the power of machine learning ? Understand discoveries on web interface and API in machine learning Who This Book Is For This book is for you if you are a JavaScript developer who wants to implement machine learning to make applications smarter, gain insightful information from the data, and enter the field of machine learning without switching to another language. Working knowledge of JavaScript language is expected to get the most out of the book. What You Will Learn ? Get an overview of state-of-the-art machine learning ? Understand the pre-processing of data handling, cleaning, and preparation ? Learn Mining and Pattern Extraction with JavaScript ? Build your own model for classification, clustering, and prediction ? Identify the most appropriate model for each type of problem ? Apply machine learning techniques to real-world applications ? Learn how JavaScript can be a powerful language for machine learning In Detail In over 20 years of existence, JavaScript has been pushing beyond the boundaries of web evolution with proven existence on servers, embedded devices, Smart TVs, IoT, Smart Cars, and more. Today, with the added advantage of machine learning research and support for JS libraries, JavaScript makes your browsers smarter than ever with the ability to learn patterns and reproduce them to become a part of innovative products and applications. Hands-on Machine Learning with JavaScript presents various avenues of machine learning in a practical and objective way, and helps implement them using the JavaScript language. Predicting behaviors, analyzing feelings, grouping data, and building neural models are some of the skills you will build from this book. You will learn how to train your machine learning models and work with different kinds of data. During this journey, you will come across use cases such as face detection, spam filtering, recommendation systems, character recognition, and more. Moreover, you will learn how to work with deep neural networks and guide your applications to gain insights from data. By the end of this book, you'll have gained hands-on knowledge on evaluating and implementing the right model, along with choosing from different JS libraries, such as NaturalNode, brain, harthur, classifier, and many more to design smarter applications. Style and approach This is a practical tutorial that uses hands-on examples to step through some real-world applications of machine learning. Without shying away from the technical details, you will explore machine learning with JavaScript using clear and practical examples.

Leverage the power of Python to build DIY robotic projects About This Book ? Design, build, and stimulate collaborative robots ? Build high-end robotics projects such as a customized personal Jarvis ? Leverage the power of Python and ROS for DIY robotic projects Who This Book Is For If building robots is your dream, then this book is made for you. Prior knowledge of Python would be an added advantage. What You Will Learn ? Get to know the basics of robotics and its functions ? Walk through interface components with microcontrollers ? Integrate robotics with the IoT environment ? Build projects using machine learning ? Implement path planning and vision processing ? Interface your robots with Bluetooth In Detail Robotics is a fast-growing industry. Multiple surveys state that investment in the field has increased tenfold in the last 6 years, and is set to become a $100-billion sector by 2020. Robots are prevalent throughout all industries, and they are all set to be a part of our domestic lives. This book starts with the installation and basic steps in configuring a robotic controller. You'll then move on to setting up your environment to use Python with the robotic controller. You'll dive deep into building simple robotic projects, such as a pet-feeding robot, and more complicated projects, such as machine learning enabled home automation system (Jarvis), vision processing based robots and a self-driven robotic vehicle using Python. By the end of this book, you'll know how to build smart robots using Python. Style and approach A simple step-by-step guide to help you learn the concepts of robotics using simple to advanced steps. You’ll not only learn the concepts of AI, machine learning, and Vision Processing, but also how to practically implement them in your projects.

Echo is a leading framework for creating web applications with the Go language. This book will show you how to develop scalable real-world web apps, RESTful services, and backend systems with Echo. About This Book ? The easiest way to learn how to build web apps with Echo ? Build a full working project ? For Go developers with only basic web development knowledge required Who This Book Is For You will need to know the basics of the Go language, and the general concepts of web development. What You Will Learn ? Key design considerations for high performance Echo applications ? How Echo handles routing ? How context is managed through the lifetime of the request and response pipeline ? Decrease complexity of your apps by developing middleware functions ? Interact with the request through request data bindings ? Interact with the response through response data renderings within the framework ? Use Echo's logging and error handling facilities ? Render Go templates within Echo to allow for server side rendering of content In Detail Echo is a leading framework for creating web applications with the Go language.? This book will show you how to develop scalable real-world web apps, RESTful services, and backend systems with Echo.? After a thorough understanding of the basics, you'll be introduced to all the concepts for a building real-world web system with Echo. You will start with the the Go HTTP standard library, and setting up your work environment. You will move on to Echo handlers, group routing, data binding, and middleware processing. After that, you will learn how to test your Go application and use templates.? By the end of this book you will be able to build your very own high performance apps using Echo. A Quick Start Guide is a focussed, shorter title which provides a faster paced introduction to a technology. They are for people who don’t need all the detail at this point in their learning curve. The presentation has been streamlined to concentrate on the things you really need to know, rather than everything. Style and approach This book creates a working example of a web application written with the Echo framework, and shows you enough of Echo to give context for a developer to bootstrap a high performance web application with the smallest amount of development time.

A hands-on guide with a minimalist and flexible approach that enables quick learning and rapid delivery of cloud-ready enterprise applications with Angular 6 About This Book ? Explore tools and techniques to push your web app to the next level ? Master Angular app design and architectural considerations ? Learn continuous integration and deploy your app on a highly available cloud infrastructure in AWS Who This Book Is For This book is for developers who want to confidently deliver high-quality and production-grade Angular apps from design to deployment. We assume that you have prior experience in writing a RESTful API with the tech stack of your choice; if you don't, you can still gain a lot of benefit from this book, which focuses on the entire scope of frontend development, from design to deployment! What You Will Learn ? Create full-stack web applications using Angular and RESTful APIs ? Master Angular fundamentals, RxJS, CLI tools, unit testing, GitHub, and Docker ? Design and architect responsive, secure and scalable apps to deploy on AWS ? Adopt a minimalist, value-first approach to delivering your app with Kanban ? Get introduced to automated testing with continuous integration on CircleCI ? Optimize Nginx and Node.js web servers with load testing tools In Detail Angular 6 for Enterprise-Ready Web Applications follows a hands-on and minimalist approach demonstrating how to design and architect high quality apps. The first part of the book is about mastering the Angular platform using foundational technologies. You will use the Kanban method to focus on value delivery, communicate design ideas with mock-up tools and build great looking apps with Angular Material. You will become comfortable using CLI tools, understand reactive programming with RxJS, and deploy to the cloud using Docker. The second part of the book will introduce you to the router-first architecture, a seven-step approach to designing and developing mid-to-large line-of-business applications, along with popular recipes. You will learn how to design a solid authentication and authorization experience; explore unit testing, early integration with backend APIs using Swagger and continuous integration using CircleCI. In the concluding chapters, you will provision a highly available cloud infrastructure on AWS and then use Google Analytics to capture user behavior. By the end of this book, you will be familiar with the scope of web development using Angular, Swagger, and Docker, learning patterns and practices to be successful as an individual developer on the web or as a team in the Enterprise. Style and approach The book follows a hands-on, value-first methodology to help readers design and architect small and large applications, while covering ancillary topics that all web developers should be aware of. The book uses minimal and flexible tools and techniques to enable quick learning and rapid delivery of high-quality and reliable Angular applications.

Be an adaptive thinker that leads the way to Artificial Intelligence About This Book ? AI-based examples to guide you in designing and implementing machine intelligence ? Develop your own method for future AI solutions ? Acquire advanced AI, machine learning, and deep learning design skills Who This Book Is For Artificial Intelligence by Example is a simple, explanatory, and descriptive guide for junior developers, experienced developers, technology consultants, and those interested in AI who want to understand the fundamentals of Artificial Intelligence and implement it practically by devising smart solutions. Prior experience with Python and statistical knowledge is essential to make the most out of this book. What You Will Learn ? Use adaptive thinking to solve real-life AI case studies ? Rise beyond being a modern-day factory code worker ? Acquire advanced AI, machine learning, and deep learning designing skills ? Learn about cognitive NLP chatbots, quantum computing, and IoT and blockchain technology ? Understand future AI solutions and adapt quickly to them ? Develop out-of-the-box thinking to face any challenge the market presents In Detail Artificial Intelligence has the potential to replicate humans in every field. This book serves as a starting point for you to understand how AI is built, with the help of intriguing examples and case studies. Artificial Intelligence By Example will make you an adaptive thinker and help you apply concepts to real-life scenarios. Using some of the most interesting AI examples, right from a simple chess engine to a cognitive chatbot, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and IoT, and develop emotional quotient in chatbots using neural networks. You will move on to designing AI solutions in a simple manner rather than get confused by complex architectures and techniques. This comprehensive guide will be a starter kit for you to develop AI applications on your own. By the end of this book, will have understood the fundamentals of AI and worked through a number of case studies that will help you develop business vision. Style and approach An easy-to-follow step by step guide which will help you get to grips with real world application of Artificial Intelligence

Develop, deploy, and streamline your data science projects with the most popular end-to-end platform, Anaconda About This Book ? Use Anaconda to find solutions for clustering, classification, and linear regression ? Analyze your data efficiently with the most powerful data science stack ? Use the Anaconda cloud to store, share, and discover projects and libraries Who This Book Is For Hands-On Data Science with Anaconda is for you if you are a developer who is looking for the best tools in the market to perform data science. It’s also ideal for data analysts and data science professionals who want to improve the efficiency of their data science applications by using the best libraries in multiple languages. Basic programming knowledge with R or Python and introductory knowledge of linear algebra is expected. What You Will Learn ? Perform cleaning, sorting, classification, clustering, regression, and dataset modeling using Anaconda ? Use the package manager conda and discover, install, and use functionally efficient and scalable packages ? Get comfortable with heterogeneous data exploration using multiple languages within a project ? Perform distributed computing and use Anaconda Accelerate to optimize computational powers ? Discover and share packages, notebooks, and environments, and use shared project drives on Anaconda Cloud ? Tackle advanced data prediction problems In Detail Anaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world. The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. You’ll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows. You’ll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod. Once you’re accustomed to all this, you’ll start with operations in data science such as cleaning, sorting, and data classification. You’ll move on to learning how to perform tasks such as clustering, regression, prediction, and building machine learning models and optimizing them. In addition to this, you’ll learn how to visualize data using the packages available for Julia, Python, and R. Style and approach This book is your step-by-step guide full of use cases, examples and illustrations to get you well-versed with the concepts of Anaconda.

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