Modernizing Drupal 10 Theme Development. Build fast, responsive Drupal websites with custom theme design to deliver a rich user experience

Luca Lusso

Working with themes in Drupal can be challenging, given the number of layers and APIs involved. Modernizing Drupal 10 Theme Development helps you explore the new Drupal 10’s theme layer in depth.With a fully implemented Drupal website on the one hand and a set of Storybook components on the other, you’ll begin by learning to create a theme from scratch to match the desired final layout. Once you’ve set up a local environment, you’ll get familiarized with design systems and learn how to map them to the structures of a Drupal website. Next, you’ll bootstrap your new theme and optimize Drupal’s productivity using tools such as webpack, Tailwind CSS, and Browsersync. As you advance, you’ll delve into all the theme layers in a step-by-step way, starting from how Drupal builds an HTML page to where the template files are and how to add custom CSS and JavaScript. You’ll also discover how to leverage all the Drupal APIs to implement robust and maintainable themes without reinventing the wheel, but by following best practices and methodologies. Toward the end, you’ll find out how to build a fully decoupled website using json:api and Next.js.By the end of this book, you’ll be able to confidently build custom Drupal themes to deliver state-of-the-art websites and keep ahead of the competition in the modern frontend world.

Machine Learning for Cybersecurity Cookbook. Over 80 recipes on how to implement machine learning algorithms for building security systems using Python

Emmanuel Tsukerman

Organizations today face a major threat in terms of cybersecurity, from malicious URLs to credential reuse, and having robust security systems can make all the difference. With this book, you'll learn how to use Python libraries such as TensorFlow and scikit-learn to implement the latest artificial intelligence (AI) techniques and handle challenges faced by cybersecurity researchers.You'll begin by exploring various machine learning (ML) techniques and tips for setting up a secure lab environment. Next, you'll implement key ML algorithms such as clustering, gradient boosting, random forest, and XGBoost. The book will guide you through constructing classifiers and features for malware, which you'll train and test on real samples. As you progress, you'll build self-learning, reliant systems to handle cybersecurity tasks such as identifying malicious URLs, spam email detection, intrusion detection, network protection, and tracking user and process behavior. Later, you'll apply generative adversarial networks (GANs) and autoencoders to advanced security tasks. Finally, you'll delve into secure and private AI to protect the privacy rights of consumers using your ML models. By the end of this book, you'll have the skills you need to tackle real-world problems faced in the cybersecurity domain using a recipe-based approach.

Getting Started with Amazon SageMaker Studio. Learn to build end-to-end machine learning projects in the SageMaker machine learning IDE

Michael Hsieh

Amazon SageMaker Studio is the first integrated development environment (IDE) for machine learning (ML) and is designed to integrate ML workflows: data preparation, feature engineering, statistical bias detection, automated machine learning (AutoML), training, hosting, ML explainability, monitoring, and MLOps in one environment.In this book, you'll start by exploring the features available in Amazon SageMaker Studio to analyze data, develop ML models, and productionize models to meet your goals. As you progress, you will learn how these features work together to address common challenges when building ML models in production. After that, you'll understand how to effectively scale and operationalize the ML life cycle using SageMaker Studio.By the end of this book, you'll have learned ML best practices regarding Amazon SageMaker Studio, as well as being able to improve productivity in the ML development life cycle and build and deploy models easily for your ML use cases.

Hands-On High Performance with Go. Boost and optimize the performance of your Golang applications at scale with resilience

Bob Strecansky

Go is an easy-to-write language that is popular among developers thanks to its features such as concurrency, portability, and ability to reduce complexity. This Golang book will teach you how to construct idiomatic Go code that is reusable and highly performant.Starting with an introduction to performance concepts, you’ll understand the ideology behind Go’s performance. You’ll then learn how to effectively implement Go data structures and algorithms along with exploring data manipulation and organization to write programs for scalable software. This book covers channels and goroutines for parallelism and concurrency to write high-performance code for distributed systems. As you advance, you’ll learn how to manage memory effectively. You’ll explore the compute unified device architecture (CUDA) application programming interface (API), use containers to build Go code, and work with the Go build cache for quicker compilation. You’ll also get to grips with profiling and tracing Go code for detecting bottlenecks in your system. Finally, you’ll evaluate clusters and job queues for performance optimization and monitor the application for performance regression.By the end of this Go programming book, you’ll be able to improve existing code and fulfill customer requirements by writing efficient programs.

Microsoft Silverlight 4 and SharePoint 2010 Integration. Techniques, practical tips, hints, and tricks for Silverlight interactions with SharePoint

Gaston C. Hillar

Silverlight is a powerful development platform for creating engaging, interactive user experiences for the Web, desktop, and mobile applications. Integrating Silverlight RIAs in SharePoint 2010 offers amazing opportunities to combine the power and flexibility offered by SharePoint. It is easy to create great user experiences when you have a step-by-step guide to implement Silverlight 4 applications on SharePoint 2010 sites.This book is not a primer on Silverlight 4 or SharePoint 2010. This book focuses on the integration of Silverlight 4 and SharePoint 2010 and provides step-by-step guidelines for implementing Silverlight RIAs in SharePoint. It is filled with real-world examples that depict the various techniques for interacting with data and services provided by this powerful business collaboration platform, for the enterprise and the Internet. As you sit reading this, you might have already started thinking about the benefits of implementing multiple Silverlight applications in a SharePoint environment. This book will help bring those thoughts to fruition.This book begins with the fundamental concepts of integrating Silverlight 4 with SharePoint 2010, such as the preparation of the development environment to create applications using Silverlight 4 and the addition of one or more Silverlight RIAs to a SharePoint site. Then, it moves on to the SharePoint Silverlight Client Object Model world, using step-by-step examples to combine a Silverlight application and a SharePoint module. It also covers methods to deploy and debug the Silverlight application while it runs as Silverlight Web Part in a SharePoint page. The book teaches you to take advantage of the new features offered by Visual Studio 2010 to browse SharePoint lists.Once the reader has control over the SharePoint Silverlight Client Object Model and its asynchronous operations in Silverlight applications, it is time to access external databases through the new Business Connectivity Services (BCS) and interact with workflows. Then, the book explains to perform CRUD operations by consuming the new SharePoint 2010 WCF Data Services in Silverlight. In the end, you'll learn to utilize Silverlight 4's rich media features to add effects and interactive animations to images and videos, thus offering the final touches to the Silverlight 4 and SharePoint 2010 integration learning experience.By the end of this book, you'll learn to take advantage of the unique features offered by Silverlight in order to create impressive UX that interact with SharePoint 2010.

PyTorch 1.x Reinforcement Learning Cookbook. Over 60 recipes to design, develop, and deploy self-learning AI models using Python

Yuxi (Hayden) Liu

Reinforcement learning (RL) is a branch of machine learning that has gained popularity in recent times. It allows you to train AI models that learn from their own actions and optimize their behavior. PyTorch has also emerged as the preferred tool for training RL models because of its efficiency and ease of use.With this book, you'll explore the important RL concepts and the implementation of algorithms in PyTorch 1.x. The recipes in the book, along with real-world examples, will help you master various RL techniques, such as dynamic programming, Monte Carlo simulations, temporal difference, and Q-learning. You'll also gain insights into industry-specific applications of these techniques. Later chapters will guide you through solving problems such as the multi-armed bandit problem and the cartpole problem using the multi-armed bandit algorithm and function approximation. You'll also learn how to use Deep Q-Networks to complete Atari games, along with how to effectively implement policy gradients. Finally, you'll discover how RL techniques are applied to Blackjack, Gridworld environments, internet advertising, and the Flappy Bird game.By the end of this book, you'll have developed the skills you need to implement popular RL algorithms and use RL techniques to solve real-world problems.

Data Ingestion with Python Cookbook. A practical guide to ingesting, monitoring, and identifying errors in the data ingestion process

Gláucia Esppenchutz

Data Ingestion with Python Cookbook offers a practical approach to designing and implementing data ingestion pipelines. It presents real-world examples with the most widely recognized open source tools on the market to answer commonly asked questions and overcome challenges.You’ll be introduced to designing and working with or without data schemas, as well as creating monitored pipelines with Airflow and data observability principles, all while following industry best practices. The book also addresses challenges associated with reading different data sources and data formats. As you progress through the book, you’ll gain a broader understanding of error logging best practices, troubleshooting techniques, data orchestration, monitoring, and storing logs for further consultation.By the end of the book, you’ll have a fully automated set that enables you to start ingesting and monitoring your data pipeline effortlessly, facilitating seamless integration with subsequent stages of the ETL process.

Building Data-Driven Applications with Danfo.js. A practical guide to data analysis and machine learning using JavaScript

Rising Odegua, Stephen Oni

Most data analysts use Python and pandas for data processing for the convenience and performance these libraries provide. However, JavaScript developers have always wanted to use machine learning in the browser as well. This book focuses on how Danfo.js brings data processing, analysis, and ML tools to JavaScript developers and how to make the most of this library to build data-driven applications.Starting with an overview of modern JavaScript, you’ll cover data analysis and transformation with Danfo.js and Dnotebook. The book then shows you how to load different datasets, combine and analyze them by performing operations such as handling missing values and string manipulations. You’ll also get to grips with data plotting, visualization, aggregation, and group operations by combining Danfo.js with Plotly. As you advance, you’ll create a no-code data analysis and handling system and create-react-app, react-table, react-chart, Draggable.js, and tailwindcss, and understand how to use TensorFlow.js and Danfo.js to build a recommendation system. Finally, you’ll build a Twitter analytics dashboard powered by Danfo.js, Next.js, node-nlp, and Twit.js.By the end of this app development book, you’ll be able to build and embed data analytics, visualization, and ML capabilities into any JavaScript app in server-side Node.js or the browser.