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Podcasts
Richard Jones, Richard Jones, Nick Abbott
Drupal 8 sets a new standard for ease of use, while offering countless new ways to tailor and deploy your content to the Web. Drupal 8 allows user to easily customize data structures, listings, and pages, and take advantage of new capabilities for displaying data on mobile devices, building APIs, and adapting to multilingual needs.The book takes you step by step through building a Drupal 8 website. Start with the basics, such as setting up a local “stack” development environment and installing your first Drupal 8 site, then move on to image and media handling, and extending Drupal modules. Push your knowledge by getting to grips with the modular nature of Drupal, and learning to extend it by adding new functionalities to create your new modules. By the end of the book, you will be able to develop and manage a modern and responsive website using Drupal.
Nagaraj Venkatesan, Ahmad Osama
The famous quote 'Data is the new oil' seems more true every day as the key to most organizations' long-term success lies in extracting insights from raw data. One of the major challenges organizations face in leveraging value out of data is building performant data engineering pipelines for data visualization, ingestion, storage, and processing. This second edition of the immensely successful book by Ahmad Osama brings to you several recent enhancements in Azure data engineering and shares approximately 80 useful recipes covering common scenarios in building data engineering pipelines in Microsoft Azure.You’ll explore recipes from Azure Synapse Analytics workspaces Gen 2 and get to grips with Synapse Spark pools, SQL Serverless pools, Synapse integration pipelines, and Synapse data flows. You’ll also understand Synapse SQL Pool optimization techniques in this second edition. Besides Synapse enhancements, you’ll discover helpful tips on managing Azure SQL Database and learn about security, high availability, and performance monitoring. Finally, the book takes you through overall data engineering pipeline management, focusing on monitoring using Log Analytics and tracking data lineage using Azure Purview.By the end of this book, you’ll be able to build superior data engineering pipelines along with having an invaluable go-to guide.
Anil Mahtani, Luis Sánchez, Enrique Fernandez Perdomo
Building and programming a robot can be cumbersome and time-consuming, but not when you have the right collection of tools, libraries, and more importantly expert collaboration. ROS enables collaborative software development and offers an unmatched simulated environment that simplifies the entire robot building process.This book is packed with hands-on examples that will help you program your robot and give you complete solutions using open source ROS libraries and tools. It also shows you how to use virtual machines and Docker containers to simplify the installation of Ubuntu and the ROS framework, so you can start working in an isolated and control environment without changing your regular computer setup.It starts with the installation and basic concepts, then continues with more complex modules available in ROS such as sensors and actuators integration (drivers), navigation and mapping (so you can create an autonomous mobile robot), manipulation, Computer Vision, perception in 3D with PCL, and more. By the end of the book, you’ll be able to leverage all the ROS Kinetic features to build a fully fledged robot for all your needs.
Vue.js is a progressive web framework for building professional user interfaces for your web applications. With Vue.js 3, the frontend framework is reinforced with architectural enhancements, new base languages, new render processes, and separated core components.The book starts with recipes for implementing Vue.js 3’s new features in your web development projects and migrating your existing Vue.js apps to the latest version. You will get up and running with TypeScript with Vue.js and find succinct solutions to common challenges and pitfalls faced in implementing components, derivatives, and animation, through to building plugins, adding state management, routing, and developing complete single-page applications (SPAs). As you advance, you'll discover recipes to help you integrate Vue.js apps with Nuxt.js in order to add server-side rendering capabilities to your SPAs. You'll then learn about the Vue.js ecosystem by exploring modern frameworks such as Quasar, Nuxt.js, Vuex, and Vuetify in your web projects. Finally, the book provides you with solutions for packaging and deploying your Vue.js apps.By the end of this Vue.js book, you'll be able to identify and solve challenges faced in building Vue.js applications and be able to adopt the Vue.js framework for frontend web projects of any scale.
Georgia Kalyva, George Kavvalakis
With AI and machine learning (ML) models gaining popularity and integrating into more and more applications, it is more important than ever to ensure that models perform accurately and are not vulnerable to cyberattacks. However, attacks can target your data or environment as well. This book will help you identify security risks and apply the best practices to protect your assets on multiple levels, from data and models to applications and infrastructure.This book begins by introducing what some common ML attacks are, how to identify your risks, and the industry standards and responsible AI principles you need to follow to gain an understanding of what you need to protect. Next, you will learn about the best practices to secure your assets. Starting with data protection and governance and then moving on to protect your infrastructure, you will gain insights into managing and securing your Azure ML workspace. This book introduces DevOps practices to automate your tasks securely and explains how to recover from ML attacks. Finally, you will learn how to set a security benchmark for your scenario and best practices to maintain and monitor your security posture.By the end of this book, you’ll be able to implement best practices to assess and secure your ML assets throughout the Azure Machine Learning life cycle.
The ability to use algorithms to solve real-world problems is a must-have skill for any developer or programmer. This book will help you not only to develop the skills to select and use an algorithm to tackle problems in the real world but also to understand how it works.You'll start with an introduction to algorithms and discover various algorithm design techniques, before exploring how to implement different types of algorithms, with the help of practical examples. As you advance, you'll learn about linear programming, page ranking, and graphs, and will then work with machine learning algorithms to understand the math and logic behind them.Case studies will show you how to apply these algorithms optimally before you focus on deep learning algorithms and learn about different types of deep learning models along with their practical use.You will also learn about modern sequential models and their variants, algorithms, methodologies, and architectures that are used to implement Large Language Models (LLMs) such as ChatGPT.Finally, you'll become well versed in techniques that enable parallel processing, giving you the ability to use these algorithms for compute-intensive tasks.By the end of this programming book, you'll have become adept at solving real-world computational problems by using a wide range of algorithms.
The automation of machine learning tasks allows developers more time to focus on the usability and reactivity of the software powered by machine learning models. TPOT is a Python automated machine learning tool used for optimizing machine learning pipelines using genetic programming. Automating machine learning with TPOT enables individuals and companies to develop production-ready machine learning models cheaper and faster than with traditional methods.With this practical guide to AutoML, developers working with Python on machine learning tasks will be able to put their knowledge to work and become productive quickly. You'll adopt a hands-on approach to learning the implementation of AutoML and associated methodologies. Complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions, this book will show you how to build automated classification and regression models and compare their performance to custom-built models. As you advance, you'll also develop state-of-the-art models using only a couple of lines of code and see how those models outperform all of your previous models on the same datasets.By the end of this book, you'll have gained the confidence to implement AutoML techniques in your organization on a production level.