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Podcasts
Jay Larry G. Johnston, Jay L Johnston
MooTools is a JavaScript framework that abstracts the JavaScript language. JavaScript itself, complex in syntax, provides the tools to write a layer of content interaction for each different browser. MooTools abstracts those individual, browser-specific layers to allow cross-browser scripting in an easy-to-read and easy-to-remember syntax.Animation and interaction, once the domain of Flash, are being taken by storm by the MooTools JavaScript framework, which can cause size, shape, color, and opacity to transition smoothly. Discover how to use AJAX to bring data to today's web page users who demand interactivity without clunky page refreshes. When searching for animation and interactivity solutions that work, MooTools 1.3 Cookbook has individual, reusable code examples that get you running fast!MooTools 1.3 Cookbook readies programmers to animate, perform AJAX, and attach event listeners in a simple format where each section provides a clear and cross-browser compatible sketch of how to solve a problem, whether reading from beginning to finish or browsing directly to a particular recipe solution.MooTools 1.3 Cookbook provides instant solutions to MooTools problems – whatever you want to do with MooTools, this book will tell you how to do it.MooTools 1.3 Cookbook is presented in a progressive order that builds concepts and ideas, while simultaneously being a collection of powerful individual, standalone, recipe solutions.
Dr. Shafat Mubin, Jichen Li, Dr. Steven Plimpton
LAMMPS is one of the most widely used tools for running simulations for research in molecular dynamics. While the tool itself is fairly easy to use, more often than not you’ll need to customize it to meet your specific simulation requirements. Extending and Modifying LAMMPS bridges this learning gap and helps you achieve this by writing custom code to add new features to LAMMPS source code. Written by ardent supporters of LAMMPS, this practical guide will enable you to extend the capabilities of LAMMPS with the help of step-by-step explanations of essential concepts, practical examples, and self-assessment questions.This LAMMPS book provides a hands-on approach to implementing associated methodologies that will get you up and running and productive in no time. You’ll begin with a short introduction to the internal mechanisms of LAMMPS, and gradually transition to an overview of the source code along with a tutorial on modifying it. As you advance, you’ll understand the structure, syntax, and organization of LAMMPS source code, and be able to write your own source code extensions to LAMMPS that implement features beyond the ones available in standard downloadable versions.By the end of this book, you’ll have learned how to add your own extensions and modifications to the LAMMPS source code that can implement features that suit your simulation requirements.
Debugging Machine Learning Models with Python is a comprehensive guide that navigates you through the entire spectrum of mastering machine learning, from foundational concepts to advanced techniques. It goes beyond the basics to arm you with the expertise essential for building reliable, high-performance models for industrial applications. Whether you're a data scientist, analyst, machine learning engineer, or Python developer, this book will empower you to design modular systems for data preparation, accurately train and test models, and seamlessly integrate them into larger technologies.By bridging the gap between theory and practice, you'll learn how to evaluate model performance, identify and address issues, and harness recent advancements in deep learning and generative modeling using PyTorch and scikit-learn. Your journey to developing high quality models in practice will also encompass causal and human-in-the-loop modeling and machine learning explainability. With hands-on examples and clear explanations, you'll develop the skills to deliver impactful solutions across domains such as healthcare, finance, and e-commerce.
The web is dead – applications now rule our online experiences. But how are you going to build them? Well, if you’ve been paying attention, you might already have tried your hand with MeteorJS, the JavaScript framework that helps you build complete full-stack web applications that are responsive and fast with ease. Mastering MeteorJS Application Development shows you how to do even more with MeteorJS – if you’re ready to try a comprehensive course through one of the most exciting frameworks in web development today, this is the book you need. Designed to take you through the entire process of building an advanced multipage application with Meteor, you’ll be able to bring your web development ideas with surprising ease. You’ll not only learn how Meteor makes web development easier, but also how you can make using Meteor easier, by automating and simplifying tasks so you can be confident you have full control of everything in your workflow – especially everything that could go wrong. From automated testing to integrating other useful frameworks such as Angular and D3, each chapter covers a crucial element in the Meteor development process.Discover how to integrate animations using Meteor’s Blaze, to give your UI designs the edge, and explore reactive programming to effectively harness RESTful systems in your projects. You will also learn how to deploy and scale your application, two crucial aspects of modern development and vital in a changing digital environment with users expecting a product and experience that delivers. With further insights on developing for mobile – and how Meteor can help you tackle the challenges of the trend – and details on incorporating SEO strategies into your application, this book isn’t just a code tutorial – it’s about creating a product that users love.
Distributed Data Systems with Azure Databricks. Create, deploy, and manage enterprise data pipelines
Microsoft Azure Databricks helps you to harness the power of distributed computing and apply it to create robust data pipelines, along with training and deploying machine learning and deep learning models. Databricks' advanced features enable developers to process, transform, and explore data. Distributed Data Systems with Azure Databricks will help you to put your knowledge of Databricks to work to create big data pipelines. The book provides a hands-on approach to implementing Azure Databricks and its associated methodologies that will make you productive in no time. Complete with detailed explanations of essential concepts, practical examples, and self-assessment questions, you’ll begin with a quick introduction to Databricks core functionalities, before performing distributed model training and inference using TensorFlow and Spark MLlib. As you advance, you’ll explore MLflow Model Serving on Azure Databricks and implement distributed training pipelines using HorovodRunner in Databricks. Finally, you’ll discover how to transform, use, and obtain insights from massive amounts of data to train predictive models and create entire fully working data pipelines. By the end of this MS Azure book, you’ll have gained a solid understanding of how to work with Databricks to create and manage an entire big data pipeline.