Publisher: K-i-s-publishing
Mastering Yii. Advance your modern web application development skills with Yii Framework 2
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
Nowadays monitoring systems play a crucial role in any IT environment. They are extensively used to not only measure your system’s performance, but also to forecast capacity issues. This is where Zabbix, one of the most popular monitoring solutions for networks and applications, comes into the picture. With an efficient monitoring system in place you’ll be able to foresee when your infrastructure runs under capacity and react accordingly. Due to the critical role a monitoring system plays, it is fundamental to implement it in the best way from its initial setup. This avoids misleading, confusing, or, even worse, false alarms which can disrupt an efficient and healthy IT department.This new edition will provide you with all the knowledge you need to make strategic and practical decisions about the Zabbix monitoring system. The setup you’ll do with this book will fit your environment and monitoring needs like a glove. You will be guided through the initial steps of choosing the correct size and configuration for your system, to what to monitor and how to implement your own custom monitoring component. Exporting and integrating your data with other systems is also covered.By the end of this book, you will have a tailor-made and well configured monitoring system and will understand with absolute clarity how crucial it is to your IT environment.
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.
Nazmus Saquib
If you are planning to create data analysis and visualization tools in the context of science, engineering, economics, or social science, then this book is for you. With this book, you will become a visualization expert, in a short time, using Mathematica.
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.