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English | 2020 | ISBN-13 : 978-1838826222 | 562 Pages | True (EPUB, MOBI) | 20.52 MB
Vue.js is a progressive web framework for building professional user interfaces for your web applications. With Vue.js 3, the frontend framework is reinforced with architectural enhancements, TypeScript as its base language, new render processes, and separated core components. This Vue.js cookbook starts with recipes for implementing new Vue.js 3 features in your web development projects and migrating your existing Vue.js apps to the latest version. It will also help you get up and running with using TypeScript with Vue.js. The book provides succinct solutions to common challenges and pitfalls in implementing components, derivatives, and animation as well as building plugins, adding state management, routing, and developing complete single-page applications (SPAs). You'll discover how you can integrate Vue.js apps with GraphQL APIs and Nuxt.js to add server-side rendering capabilities to your SPAs. You'll also understand the Vue.js ecosystem by exploring modern frameworks such as Quasar, Nuxt.js, Vuex, and Vuetify in your web projects. Finally, you’ll learn how to effectively package and test your web apps, with features such as internationalization (i18n) and form-validation, and deploy them to Netlify and AWS cloud.
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English | 2020 | ISBN-13 : 978-1838640859 | 432 Pages | True (EPUB, MOBI)| 188 MB
With information on the web exponentially increasing, it has become more difficult than ever to navigate through everything to find reliable content that will help you get started with deep learning (DL). This book is designed to help you if you're a beginner looking to work on deep learning and build deep learning models from scratch, and already have the basic mathematical and programming knowledge required to get started. The book begins with a basic overview of machine learning, guiding you through setting up popular Python frameworks. You will also understand how to prepare data by cleaning and preprocessing it for deep learning, and gradually go on to explore neural networks. A dedicated section will give you insights into the working of neural networks by helping you get hands-on with training single and multiple layers of neurons. Later, you will cover popular neural network architectures such as CNNs, RNNs, AEs, VAEs, and GANs with the help of simple examples and even build models from scratch. At the end of each chapter, you will find a question and answer section to help you test what you've learned through the course of the book.
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