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Podcasts
Apache Arrow is designed to accelerate analytics and allow the exchange of data across big data systems easily.In-Memory Analytics with Apache Arrow begins with a quick overview of the Apache Arrow format, before moving on to helping you to understand Arrow’s versatility and benefits as you walk through a variety of real-world use cases. You'll cover key tasks such as enhancing data science workflows with Arrow, using Arrow and Apache Parquet with Apache Spark and Jupyter for better performance and hassle-free data translation, as well as working with Perspective, an open source interactive graphical and tabular analysis tool for browsers. As you advance, you'll explore the different data interchange and storage formats and become well-versed with the relationships between Arrow, Parquet, Feather, Protobuf, Flatbuffers, JSON, and CSV. In addition to understanding the basic structure of the Arrow Flight and Flight SQL protocols, you'll learn about Dremio’s usage of Apache Arrow to enhance SQL analytics and discover how Arrow can be used in web-based browser apps. Finally, you'll get to grips with the upcoming features of Arrow to help you stay ahead of the curve.By the end of this book, you will have all the building blocks to create useful, efficient, and powerful analytical services and utilities with Apache Arrow.
Matt Harrison, Theodore Petrou
The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands as one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through situations that you are highly likely to encounter.This new updated and revised edition provides you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way. Many advanced recipes combine several different features across the pandas library to generate results.
Pro Tools HD is a digital audio workstation platform for Microsoft Windows and Mac OS X operating systems. It is the leading audio software when it comes to professional audio work. Working effectively with audio and producing professional music with Pro Tools HD is not an easy task.Beginning with what the software is about, we will take you all the way through to the steps required to efficiently record your audio. You will discover how to improve the workflow of Pro Tools software and receive innovative tips to enable flawless editing in music production, film scoring, film, and television post-production.Packed with concise and clear instructions on using Pro Tools HD: Advanced Techniques and Workflows, this book starts with different possible hardware and software combinations to help you understand the strengths and limitations of each, before taking you through powerful editing and advanced mixing techniques.When it comes to choosing a ProTools HD system there are different technologies available and therefore, many ways to use the system optimally so, you will learn about some digital audio concepts for better software optimisation. You will then learn editing using Beat detective, as well as covering excellent workflow and routing concepts to take full advantage of ProTools mixing capabilities, integrating both hardware analogue units with your favorite plugins. Finally, you will see how you can export your project safer, faster and better.This guide shows you the framework to enable you to take your usage of ProTools to the next level by explaining and discussing new and advanced features to achieve industry standard techniques.
Learn LLVM 12. A beginner's guide to learning LLVM compiler tools and core libraries with C++
LLVM was built to bridge the gap between compiler textbooks and actual compiler development. It provides a modular codebase and advanced tools which help developers to build compilers easily. This book provides a practical introduction to LLVM, gradually helping you navigate through complex scenarios with ease when it comes to building and working with compilers.You’ll start by configuring, building, and installing LLVM libraries, tools, and external projects. Next, the book will introduce you to LLVM design and how it works in practice during each LLVM compiler stage: frontend, optimizer, and backend. Using a subset of a real programming language as an example, you will then learn how to develop a frontend and generate LLVM IR, hand it over to the optimization pipeline, and generate machine code from it. Later chapters will show you how to extend LLVM with a new pass and how instruction selection in LLVM works. You’ll also focus on Just-in-Time compilation issues and the current state of JIT-compilation support that LLVM provides, before finally going on to understand how to develop a new backend for LLVM.By the end of this LLVM book, you will have gained real-world experience in working with the LLVM compiler development framework with the help of hands-on examples and source code snippets.
Sherin Thomas, Sudhanshu Passi
PyTorch Deep Learning Hands-On is a book for engineers who want a fast-paced guide to doing deep learning work with PyTorch. It is not an academic textbook and does not try to teach deep learning principles. The book will help you most if you want to get your hands dirty and put PyTorch to work quickly.PyTorch Deep Learning Hands-On shows how to implement the major deep learning architectures in PyTorch. It covers neural networks, computer vision, CNNs, natural language processing (RNN), GANs, and reinforcement learning. You will also build deep learning workflows with the PyTorch framework, migrate models built in Python to highly efficient TorchScript, and deploy to production using the most sophisticated available tools.Each chapter focuses on a different area of deep learning. Chapters start with a refresher on how the model works, before sharing the code you need to implement it in PyTorch.This book is ideal if you want to rapidly add PyTorch to your deep learning toolset.
Mireia Alegre Ruiz, Emilio Rodriguez Martinez
Lottie is a small and scalable JSON-based animation file. LottieFiles is the platform where Lottie animations can be uploaded, tested, and shared. By combining the LottieFiles plugin and the LottieFiles platform, you’ll be able to create stunning animations that are easy to integrate in any device. You’ll also see how to use the Bodymovin plugin in After Effects to export your animation to a JSON file.The book starts by giving you an overview of Lottie and LottieFiles. As you keep reading, you’ll understand the entire Lottie ecosystem and get hands-on with classic 2D animation principles. You’ll also get a step-by-step guided tour to ideate, sketch for storytelling, design an icon that will fulfill the needs and expectations of users based on UX, and finally animate it in Adobe After Effects. This will help you get familiar with the After Effects environment, work with vector shape layers, create and modify keyframes using layer properties, explore path and mask features, and adjust timing easily to create professional-looking animations.By the end of this animation book, you’ll be able to create and export your own Lottie animations using After Effects and implement them in mobile apps using React Native. You’ll also have an understanding of 2D animation best practices and principles that you can apply in your own projects.
Learn T-SQL Querying. A guide to developing efficient and elegant T-SQL code - Second Edition
Data professionals seeking to excel in Transact-SQL for Microsoft SQL Server and Azure SQL Database often lack comprehensive resources. Learn T-SQL Querying second edition focuses on indexing queries and crafting elegant T-SQL code enabling data professionals gain mastery in modern SQL Server versions (2022) and Azure SQL Database. The book covers new topics like logical statement processing flow, data access using indexes, and best practices for tuning T-SQL queries.Starting with query processing fundamentals, the book lays a foundation for writing performant T-SQL queries. You’ll explore the mechanics of the Query Optimizer and Query Execution Plans, learning to analyze execution plans for insights into current performance and scalability. Using dynamic management views (DMVs) and dynamic management functions (DMFs), you’ll build diagnostic queries. The book covers indexing and delves into SQL Server’s built-in tools to expedite resolution of T-SQL query performance and scalability issues. Hands-on examples will guide you to avoid UDF pitfalls and understand features like predicate SARGability, Query Store, and Query Tuning Assistant. By the end of this book, you‘ll have developed the ability to identify query performance bottlenecks, recognize anti-patterns, and avoid pitfalls