This book is geared toward a designer who wants to explore the world of application development. If you do not know anything about design, that’s OK! We will walk you through step by step on how to build your first native iOS or Android app in the fastest and easiest way possible. Using free and open source software, this book will get you up and running quickly and efficiently--start using Parse and PhoneGap today with this key title.
What You’ll Learn
Explore the capabilities and UI widgets it provides and the features that make it stand out from its competitorsBuild one web technology-based app that works on both desktops and mobile devices (Android and iOS)Create and hook a Webix app up to a Node.js/Express-based RESTful server API for data storageMobilize a Webix app using both PhoneGap and Progressive Web App techniquesEnhance your Webix and general development skills in the most fun way possible: by building a game
Moderately experienced front-end developers who want to learn about Webix and the power it brings to client-side development.
Developers looking to use their web development skills to build cross-platform apps that work on both desktop and mobile devices with Webix as the foundation.
A working knowledge of CSS, HTML and JavsScript is assumed, though you don’t need to be an expert.
With Getting to Know Vue.js, you'll see how to combine reusable code with custom components, allowing you to create snippets of reusable code to suit your specific business needs. You'll also explore how to use Single File Components and the Vue.js Command Line Interface (CLI) to build components in a single file and add in build tools as you see fit.
What You'll Learn
Electron: From Beginner to Pro guides you through the capabilities that you have available to create desktop applications. Learn to use features like file system access, create native menus, OS-specific dialogs and more. The authors will show you how to package your application for distribution for multiple platforms and enable auto-updating.
Developers wanting to leverage existing a Web application to extend functionality with a desktop application.
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.
By using concrete examples, minimal theory, and two production-ready Python frameworks—scikit-learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.Explore the machine learning landscape, particularly neural netsUse scikit-learn to track an example machine-learning project end-to-endExplore several training models, including support vector machines, decision trees, random forests, and ensemble methodsUse the TensorFlow library to build and train neural netsDive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learningLearn techniques for training and scaling deep neural netsApply practical code examples without acquiring excessive machine learning theory or algorithm details
Windows Vista Sidebar is a panel located on the desktop of a PC where gadgets can be placed for easy access and reference. These gadgets are small, single-purpose applications, such as clocks, calendars, games, RSS notifiers, search tools, stock tickers, etc, that reside on the Windows desktop and on the Windows Sidebar. The book will be a tutorial to design and develop a gadget. It will provide ready-to-use samples using .NET, XML, CSS and AJAX. After reading the book, a web developer/designer will be confident enough to start developing gadgets for Windows Vista Sidebar. The beginner portion of the book shows an overview of the subject with the design pattern, the architecture and implementation details. The later sections will have solid examples for instant results. In short, the book will tell how to do everything with Sidebar Gadgets using solid, unique examples. Brief outline: " Brief background on Gadgets " Define architecture, design consideration and implementation to give a clear view to the developer " Step by step, create a useful Gadget sample "My Blogs" " Elaborate the architecture design constraint and implementation details for the sample " Detail the standard practices " Recheck the gadget created for standard practices " Improvise and Improve with compare and contrast " Add advanced samples with .NET, AJAX and XHTML.
Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way.
You’ll learn how to:Wrangle—transform your datasets into a form convenient for analysisProgram—learn powerful R tools for solving data problems with greater clarity and easeExplore—examine your data, generate hypotheses, and quickly test themModel—provide a low-dimensional summary that captures true "signals" in your datasetCommunicate—learn R Markdown for integrating prose, code, and results
Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.Use the IPython shell and Jupyter notebook for exploratory computingLearn basic and advanced features in NumPy (Numerical Python)Get started with data analysis tools in the pandas libraryUse flexible tools to load, clean, transform, merge, and reshape dataCreate informative visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsAnalyze and manipulate regular and irregular time series dataLearn how to solve real-world data analysis problems with thorough, detailed examples