Wydawca: Packt Publishing
Ed Snider
Discover how to extend and build upon the components of the Xamarin.Forms toolkit to develop an effective, robust mobile app architecture. Starting with an app built with the basics of the Xamarin.Forms toolkit, we’ll go step by step through several advanced topics to create a solution architecture rich with the benefits of good design patterns and best practices.We’ll start by introducing a core separation between the app’s user interface and the app’s business logic by applying the MVVM pattern and data binding. Discover how to extend and build upon the components of the Xamarin.Forms toolkit to develop an effective, robust mobile app architecture. Starting with an app built with the basics of the Xamarin.Forms toolkit, we’ll go step by step through several advanced topics to create a solution architecture rich with the benefits of good design patterns and best practices.We’ll start by introducing a core separation between the app’s user interface and the app’s business logic by applying the MVVM pattern and data binding. Then we will focus on building out a layer of plugin-like services that handle platform-specific utilities such as navigation, geo-location, and the camera, as well as how to use these services with inversion of control and dependency injection. Next we’ll connect the app to a live web-based API and set up offline synchronization. Then, we’ll dive into testing the app—both the app logic through unit tests and the user interface using Xamarin’s UITest framework. Finally, we’ll integrate Xamarin Insights for monitoring usage and bugs to gain a proactive edge on app quality.
Ed Snider
Discover how to extend and build upon the components of the Xamarin.Forms toolkit to develop effective, robust mobile app architecture. Starting with an app built with the basics of the Xamarin.Forms toolkit, we'll go step by step through several advanced topics to create a solution architecture rich with the benefits of good design patterns and best practices.We'll start by introducing a core separation between the app's user interface and the app's business logic by applying the MVVM pattern and data-binding. Then we will focus on building out a layer of plugin-like services that handle platform-specific utilities such as navigation and geo-location, as well as how to loosely use these services in the app with inversion of control and dependency injection. Next we'll connect the app to a live web-based API and set up offline synchronization. Then, we'll dive into testing the app logic through unit tests. Finally, we will setup Visual Studio App Center to automate building, testing, distributing and monitoring the app.
Sunny Jha
Citrix® XenApp® is one of the leading pieces of Application delivery software that delivers Windows compatible apps to users on any device, anywhere. Citrix® XenApp® also gives administrators the ability to manage and control the freedom of mobility by increasing the security and saving costs at the same time.This book will provide you with all the knowledge required to successfully deploy and master a complete Citrix® hosted application. First, it will cover essential concepts of the architecture of XenApp®. You will then learn how to set up Hypervisor and how to set up Infrastructure components. Next you will learn how to Set up Citrix® Components, XenApp® resources, PVS, and Netscaler. We will further look at how to prepare the environment for Rollout. Additionally, you will learn how to configure the Citrix® components such as Citrix® Director. Moreover, you’ll learn about shared desktop for delivery to end users and the application of policies for effective and secure delivery. Finally, you will learn how to implement provisioning services for a Citrix® XenApp® 7.6 environment.
Mastering Yii. Click here to enter text
Charles R. Portwood ll
The successor of Yii Framework 1.1, Yii 2 is a complete rewrite of Yii Framework, one of the most popular PHP 5 frameworks around for making modern web applications. The update embraces the best practices and protocols established with newer versions of PHP, while still maintaining the simple, fast, and extendable behavior found in its predecessor.This book has been written to enhance your skills and knowledge with Yii Framework 2. Starting with configuration and how to initialize new projects, you’ll learn how to configure, manage, and use every aspect of Yii2 from Gii, DAO, Query Builder, Active Record, and migrations, to asset manager. You'll also discover how to automatically test your code using codeception.With this book by your side, you’ll have all the skills you need to quickly create rich modern web and console applications with Yii 2.
Andrea Dalle Vacche, Andrea Dalle Vacche, Stefano...
Mastering Zendesk. Click here to enter text
Cedric F. Jacob
Zendesk is a cloud-based customer service solution that is widely used because it is easy, efficienct, flexible, and low cost. It is highly scalable and is great for organizations of all sizes. If you’re a Zendesk administrator and are looking to explore advanced-level concepts, then this book is for you. It covers the core functionalities such as managing users, groups, and the organization, and creating and adding custom fields. You will learn how to add customized ticket channels to your account. Then, you will focus on customizing business rules and extending Zendesk with JIRA and Salesforce. Towards the end, the book emphasizes security and troubleshooting aspects as well as providing tips and tricks to create a more efficient support environment.By the end of this book, you will be able to turn a basic Zendesk setup into a highly customized working environment.
Sergiy Suchok
There are many algorithms for data analysis and it’s not always possible to quickly choose the best one for each case. Implementation of the algorithms takes a lot of time. With the help of Mathematica, you can quickly get a result from the use of a particular method, because this system contains almost all the known algorithms for data analysis.If you are not a programmer but you need to analyze data, this book will show you the capabilities of Mathematica when just few strings of intelligible code help to solve huge tasks from statistical issues to pattern recognition. If you're a programmer, with the help of this book, you will learn how to use the library of algorithms implemented in Mathematica in your programs, as well as how to write algorithm testing procedure.With each chapter, you'll be more immersed in the special world of Mathematica. Along with intuitive queries for data processing, we will highlight the nuances and features of this system, allowing you to build effective analysis systems.With the help of this book, you will learn how to optimize the computations by combining your libraries with the Mathematica kernel.
Penny de Byl
Mathematics is an essential skill when it comes to graphics and game development, particularly if you want to understand the generation of real-time computer graphics and the manipulation of objects and environments in a detailed way. Python, together with Pygame and PyOpenGL, provides you with the opportunity to explore these features under the hood, revealing how computers generate and manipulate 3D environments. Mathematics for Game Programming and Computer Graphics is an exhaustive guide to getting “back to the basics” of mathematics, using a series of problem-based, practical exercises to explore ideas around drawing graphic lines and shapes, applying vectors and vertices, constructing and rendering meshes, and working with vertex shaders. By leveraging Python, Pygame, and PyOpenGL, you’ll be able to create your own mathematics-based engine and API that will be used throughout to build applications. By the end of this graphics focussed book, you’ll have gained a thorough understanding of how essential mathematics is for creating, rendering, and manipulating 3D virtual environments and know the secrets behind today’s top graphics and game engines.
Tivadar Danka, Santiago Valdarrama
Mathematics of Machine Learning provides a rigorous yet accessible introduction to the mathematical underpinnings of machine learning, designed for engineers, developers, and data scientists ready to elevate their technical expertise. With this book, you’ll explore the core disciplines of linear algebra, calculus, and probability theory essential for mastering advanced machine learning concepts. PhD mathematician turned ML engineer Tivadar Danka—known for his intuitive teaching style that has attracted 100k+ followers—guides you through complex concepts with clarity, providing the structured guidance you need to deepen your theoretical knowledge and enhance your ability to solve complex machine learning problems. Balancing theory with application, this book offers clear explanations of mathematical constructs and their direct relevance to machine learning tasks. Through practical Python examples, you’ll learn to implement and use these ideas in real-world scenarios, such as training machine learning models with gradient descent or working with vectors, matrices, and tensors. By the end of this book, you’ll have gained the confidence to engage with advanced machine learning literature and tailor algorithms to meet specific project requirements.*Email sign-up and proof of purchase required
MATLAB for Machine Learning. Practical examples of regression, clustering and neural networks
Giuseppe Ciaburro
MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners.You’ll start by getting your system ready with t he MATLAB environment for machine learning and you’ll see how to easily interact with the Matlab workspace. We’ll then move on to data cleansing, mining and analyzing various data types in machine learning and you’ll see how to display data values on a plot. Next, you’ll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You’ll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you’ll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB.
Giuseppe Ciaburro
Discover why the MATLAB programming environment is highly favored by researchers and math experts for machine learning with this guide which is designed to enhance your proficiency in both machine learning and deep learning using MATLAB, paving the way for advanced applications.By navigating the versatile machine learning tools in the MATLAB environment, you’ll learn how to seamlessly interact with the workspace. You’ll then move on to data cleansing, data mining, and analyzing various types of data in machine learning, and visualize data values on a graph. As you progress, you’ll explore various classification and regression techniques, skillfully applying them with MATLAB functions.This book teaches you the essentials of neural networks, guiding you through data fitting, pattern recognition, and cluster analysis. You’ll also explore feature selection and extraction techniques for performance improvement through dimensionality reduction. Finally, you’ll leverage MATLAB tools for deep learning and managing convolutional neural networks.By the end of the book, you’ll be able to put it all together by applying major machine learning algorithms in real-world scenarios.
Matplotlib 2.x By Example. Multi-dimensional charts, graphs, and plots in Python
Allen Yu, Claire Chung, Aldrin Yim
Big data analytics are driving innovations in scientific research, digital marketing, policy-making and much more. Matplotlib offers simple but powerful plotting interface, versatile plot types and robust customization.Matplotlib 2.x By Example illustrates the methods and applications of various plot types through real world examples. It begins by giving readers the basic know-how on how to create and customize plots by Matplotlib. It further covers how to plot different types of economic data in the form of 2D and 3D graphs, which give insights from a deluge of data from public repositories, such as Quandl Finance. You will learn to visualize geographical data on maps and implement interactive charts.By the end of this book, you will become well versed with Matplotlib in your day-to-day work to perform advanced data visualization. This book will guide you to prepare high quality figures for manuscripts and presentations. You will learn to create intuitive info-graphics and reshaping your message crisply understandable.
Srinivasa Rao Poladi
Matplotlib provides a large library of customizable plots, along with a comprehensive set of backends. Matplotlib 3.0 Cookbook is your hands-on guide to exploring the world of Matplotlib, and covers the most effective plotting packages for Python 3.7. With the help of this cookbook, you'll be able to tackle any problem you might come across while designing attractive, insightful data visualizations. With the help of over 150 recipes, you'll learn how to develop plots related to business intelligence, data science, and engineering disciplines with highly detailed visualizations. Once you've familiarized yourself with the fundamentals, you'll move on to developing professional dashboards with a wide variety of graphs and sophisticated grid layouts in 2D and 3D. You'll annotate and add rich text to the plots, enabling the creation of a business storyline. In addition to this, you'll learn how to save figures and animations in various formats for downstream deployment, followed by extending the functionality offered by various internal and third-party toolkits, such as axisartist, axes_grid, Cartopy, and Seaborn. By the end of this book, you'll be able to create high-quality customized plots and deploy them on the web and on supported GUI applications such as Tkinter, Qt 5, and wxPython by implementing real-world use cases and examples.
Aldrin Yim, Claire Chung, Allen Yu
Python is a general-purpose programming language increasingly being used for data analysis and visualization. Matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the Matplotlib library. Matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with Matplotlib. After that, you’ll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You’ll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book. Further on, you’ll explore Matplotlib 2.1.x on the web, from a cloud-based platform using third-party packages such as Django. Finally, you will integrate interactive, real-time visualization techniques into your current workflow with the help of practical real-world examples.By the end of this book, you’ll be thoroughly comfortable with using the popular Python data visualization library Matplotlib 2.1.x and leveraging its power to build attractive, insightful, and powerful visualizations.
Sandro Tosi, John Hunter, Sandro Tosi
Providing appealing plots and graphs is an essential part of various fields such as scientific research, data analysis, and so on. Matplotlib, the Python 2D plotting library, is used to produce publication-quality figures in a variety of hardcopy formats and interactive environments across platforms. This book explains creating various plots, histograms, power spectra, bar charts, error charts, scatter-plots and much more using the powerful Matplotlib library to get impressive out-of-the-box results.This book gives you a comprehensive tour of the key features of the Matplotlib Python 2D plotting library, right from the simplest concepts to the most advanced topics. You will discover how easy it is to produce professional-quality plots when you have this book to hand.The book introduces the library in steps. First come the basics: introducing what the library is, its important prerequisites (and terminology), installing and configuring Matplotlib, and going through simple plots such as lines, grids, axes, and charts. Then we start with some introductory examples, and move ahead by discussing the various programming styles that Matplotlib allows, and several key features.Further, the book presents an important section on embedding applications. You will be introduced to three of the best known GUI libraries 'GTK+, Qt, and wxWidgets' and presented with the steps to implement to include Matplotlib in an application written using each of them. You will learn through an incremental approach: from a simple example that presents the peculiarities of the GUI library, to more complex ones, using GUI designer tools.Because the Web permeates all of our activities, a part of the book is dedicated to showing how Matplotlib can be used in a web environment, and another section focuses on using Matplotlib with common Python web frameworks, namely, Pylons and Django. Last, but not least, you will go through real-world examples, where you will see some real situations in which you can use Matplotlib.