PrestaShop Module Development. Develop and customize powerful modules for PrestaShop 1.5 and 1.6

Fabien Serny

Machine Learning for Time-Series with Python. Use Python to forecast, predict, and detect anomalies with state-of-the-art machine learning methods - Second Edition

Ben Auffarth

The Python time-series ecosystem is a huge and challenging topic to tackle, especially for time series since there are so many new libraries and models. Machine Learning for Time Series, Second Edition, aims to deepen your understanding of time series by providing a comprehensive overview of popular Python time-series packages and helping you build better predictive systems.This fully updated second edition starts by re-introducing the basics of time series and then helps you get to grips with traditional autoregressive models as well as modern non-parametric models. By observing practical examples and the theory behind them, you will gain a deeper understanding of loading time-series datasets from any source and a variety of models, such as deep learning recurrent neural networks, causal convolutional network models, and gradient boosting with feature engineering. This book will also help you choose the right model for the right problem by explaining the theory behind several useful models. New updates include a chapter on forecasting and extracting signals on financial markets and case studies with relevant examples from operations management, digital marketing, and healthcare.By the end of this book, you should feel at home with effectively analyzing and applying machine learning methods to time series.

Enhanced Test Automation with WebdriverIO. Unlock the superpowers of hybrid testing frameworks

Paul M. Grossman, Larry C. Goddard, Angie Jones

This book helps you embark on a comprehensive journey to master the art of WebdriverIO automation, from installation through to advanced framework development.You’ll start by following step-by-step instructions on installing WebdriverIO, configuring Node packages, and creating a simple test. Here you’ll gain an understanding of the mechanics while also learning to add reporting and screen captures to your test results to enhance your test case documentation. In the next set of chapters, you’ll delve into the intricacies of configuring and developing robust method wrappers, a crucial skill for supporting multiple test suites. The book goes beyond the basics, exploring testing techniques tailored for Jenkins as well as LambdaTest cloud environments. As you progress, you’ll gain a deep understanding of both TypeScript and JavaScript languages and acquire versatile coding skills.By the end of this book, you’ll have developed the expertise to construct a sophisticated test automation framework capable of executing an entire suite of tests using WebdriverIO in either TypeScript or JavaScript, as well as excel in your test automation endeavors and deliver reliable, efficient testing solutions.

Deep Learning with MXNet Cookbook. Discover an extensive collection of recipes for creating and implementing AI models on MXNet

Andrés P. Torres, Paul Newman

Explore the capabilities of the open-source deep learning framework MXNet to train and deploy neural network models and implement state-of-the-art (SOTA) architectures in Computer Vision, natural language processing, and more. The Deep Learning with MXNet Cookbook is your gateway to constructing fast and scalable deep learning solutions using Apache MXNet.Starting with the different versions of MXNet, this book helps you choose the optimal version for your use and install your library. You’ll work with MXNet/Gluon libraries to solve classification and regression problems and gain insights into their inner workings. Venturing further, you’ll use MXNet to analyze toy datasets in the areas of numerical regression, data classification, picture classification, and text classification. From building and training deep-learning neural network architectures from scratch to delving into advanced concepts such as transfer learning, this book covers it all. You'll master the construction and deployment of neural network architectures, including CNN, RNN, LSTMs, and Transformers, and integrate these models into your applications.By the end of this deep learning book, you’ll wield the MXNet and Gluon libraries to expertly create and train deep learning networks using GPUs and deploy them in different environments.

Python Data Visualization Cookbook. As a developer with knowledge of Python you are already in a great position to start using data visualization. This superb cookbook shows you how in plain language and practical recipes, culminating with 3D animations

Igor Milovanovic

Today, data visualization is a hot topic as a direct result of the vast amount of data created every second. Transforming that data into information is a complex task for data visualization professionals, who, at the same time, try to understand the data and objectively transfer that understanding to others. This book is a set of practical recipes that strive to help the reader get a firm grasp of the area of data visualization using Python and its popular visualization and data libraries.Python Data Visualization Cookbook will progress the reader from the point of installing and setting up a Python environment for data manipulation and visualization all the way to 3D animations using Python libraries. Readers will benefit from over 60 precise and reproducible recipes that guide the reader towards a better understanding of data concepts and the building blocks for subsequent and sometimes more advanced concepts.Python Data Visualization Cookbook starts by showing you how to set up matplotlib and the related libraries that are required for most parts of the book, before moving on to discuss some of the lesser-used diagrams and charts such as Gantt Charts or Sankey diagrams. During the book, we go from simple plots and charts to more advanced ones, thoroughly explaining why we used them and how not to use them. As we go through the book, we will also discuss 3D diagrams. We will peep into animations just to show you what it takes to go into that area. Maps are irreplaceable for displaying geo-spatial data, so we also show you how to build them. In the last chapter, we show you how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python.This book will help those who already know how to program in Python to explore a new field – one of data visualization. As this book is all about recipes that explain how to do something, code samples are abundant, and they are followed by visual diagrams and charts to help you understand the logic and compare your own results with what is explained in the book.

Sakai CLE Courseware Management: The Official Guide. Take your e-learning, research, and collaboration experience to the next level

Alan Mark Berg, Ian Dolphin, Sakai Foundation, Sakai Foundation (Project)

Sakai is a Collaboration and Learning environment that provides the means to manage users, courses, instructors, and facilities, as well as a spectrum of tools including assessment, grading, and messaging. Sakai is loaded with many handy features and tools, which make it uniquely the Learning system of the present as well as the future.This book is the officially endorsed Sakai guide and is an update to the previous book, Sakai Courseware Management: The Official Guide. From setting up and running Sakai for the first time to creatively using its tools and features, this book delivers everything you need to know.Written by Alan Berg, a Sakai fellow and former Quality Assurance Director of the Sakai Foundation and Ian Dolphin the Executive Director of the Sakai Foundation with significant contributions from the Sakai community, Sakai CLE Courseware Management: The Official Guide is a comprehensive study of how Sakai CLE should be used, managed, and maintained, with real world examples and practical explanations.The book opens with an overview of Sakai, its history and how to set up a demonstration version. Next, the underlying structures and tools are described. In using Sakai for Teaching and Collaboration, there is a detailed discussion of how to structure online courses for teaching and collaboration between groups of students, from creating course sites to understanding their use in different organizations around the world.

Odoo 11 Development Essentials. Develop and customize business applications with Odoo 11 - Third Edition

Daniel Reis

Odoo continues to gain worldwide momentum as the best platform for open source ERP installations. Now, with Odoo 11, you have access to an improved GUI, performance optimization, integrated in-app purchase features, and a fast-growing community to help transform and modernize your business. With this practical guide, you will cover all the new features that Odoo 11 has to offer to build and customize business applications, focusing on the publicly available community edition.We begin with setting up a development environment, and as you make your way through the chapters, you will learn to build feature-rich business applications. With the aim of jump-starting your Odoo proficiency level, from no specific knowledge to application development readiness, you will develop your first Odoo application. We then move on to topics such as models and views, and understand how to use server APIs to add business logic, helping to lay a solid foundation for advanced topics.The book concludes with Odoo interactions and how to use the Odoo API from other programs, all of which will enable you to efficiently integrate applications with other external systems.

Mastering Python for Finance. Understand, design, and implement state-of-the-art mathematical and statistical applications used in finance with Python

WEIMING MA, James Ma Weiming