Deep Learning with R, 2nd EditionDeep Learning with R, 2nd Edition shows you how to put deep learning into action. It's based on the revised new edition of François Chollet's bestselling Deep Learning with Python. All code and examples have been expertly translated to the R language by Tomasz Kalinowski, who maintains the Keras and Tensorflow R packages at RStudio. Novices and experienced ML practitioners will love the expert insights, practical techniques, and important theory for building neural networks.
Deep learning has become essential knowledge for data scientists, researchers, and software developers. The R language APIs for Keras and TensorFlow put deep learning within reach for all R users, even if they have no experience with advanced machine learning or neural networks. This book shows you how to get started on core DL tasks like computer vision, natural language processing, and more using R.
Deep Learning with R, 2nd Edition is a hands-on guide to deep learning using the R language. As you move thr ...
Effective Data Science InfrastructureEffective Data Science Infrastructure: How to make data scientists more productive is a hands-on guide to assembling infrastructure for data science and machine learning applications. It reveals the processes used at Netflix and other data-driven companies to manage their cutting edge data infrastructure. In it, you'll master scalable techniques for data storage, computation, experiment tracking, and orchestration that are relevant to companies of all shapes and sizes. You'll learn how you can make data scientists more productive with your existing cloud infrastructure, a stack of open source software, and idiomatic Python.
The author is donating proceeds from this book to charities that support women and underrepresented groups in data science.
Growing data science projects from prototype to production requires reliable infrastructure. Using the powerful new techniques and tooling in this book, you can stand up an infrastructure stack that will scale with any organization, from ...
Data-Oriented ProgrammingData-Oriented Programming is a one-of-a-kind guide that introduces the data-oriented paradigm. This groundbreaking approach represents data with generic immutable data structures. It simplifies state management, eases concurrency, and does away with the common problems you'll find in object-oriented code. The book presents powerful new ideas through conversations, code snippets, and diagrams that help you quickly grok what's great about DOP. Best of all, the paradigm is language-agnostic - you'll learn to write DOP code that can be implemented in JavaScript, Ruby, Python, Clojure, and also in traditional OO languages like Java or C#.
Code that combines behavior and data, as is common in object-oriented designs, can introduce almost unmanageable complexity for state management. The Data-oriented programming (DOP) paradigm simplifies state management by holding application data in immutable generic data structures and then performing calculations using non-mutating general-purpose fun ...
Pro Data Mashup for Power BIThis book provides all you need to find data from external sources and load and transform that data into Power BI where you can mine it for business insights and a competitive edge. This ranges from connecting to corporate databases such as Azure SQL and SQL Server to file-based data sources, and cloud- and web-based data sources. The book also explains the use of Direct Query and Live Connect to establish instant connections to databases and data warehouses and avoid loading data.
The book provides detailed guidance on techniques for transforming inbound data into normalized data sets that are easy to query and analyze. This covers data cleansing, data modification, and standardization as well as merging source data into robust data structures that can feed into your data model. You will learn how to pivot and transpose data and extrapolate missing values as well as harness external programs such as R and Python into a Power Query data flow. You also will see how to handle errors ...
Azure Web Apps for DevelopersAzure Web Apps is a fully managed platform that you can use to build mission-critical web applications that are highly available, secure, and scalable to global proportions. Combined with first-class tooling from Visual Studio and the Microsoft Azure Tools, the Azure Web Apps service is the fastest way to get your web application to production. Azure Web Apps is part of the Azure App Service that is designed to empower developers to build web and mobile applications for any device.
Developing web applications to host on Azure Web Apps is a familiar experience for developers accustomed to hosting web applications on Internet Information Services (IIS). Developers can use ASP.NET, Java, Node.js, PHP, and Python for their application development locally and easily deploy to Azure Web Apps. The environment supports continuous deployment to multiple staging environments, enabling development teams to deploy application updates rapidly and reliably.
Azure Web Apps is more than a host f ...
SQL Antipatterns, Volume 1SQL is the ubiquitous language for software developers working with structured data. Most developers who rely on SQL are experts in their favorite language (such as Java, Python, or Go), but they're not experts in SQL. They often depend on antipatterns - -solutions that look right but become increasingly painful to work with as you uncover their hidden costs. Learn to identify and avoid many of these common blunders. Refactor an inherited nightmare into a data model that really works. Updated for the current versions of MySQL and Python, this new edition adds a dozen brand new mini-antipatterns for quick wins.
No matter which platform, framework, or language you use, the database is the foundation of your application, and the SQL database language is the standard for working with it. Antipatterns are solutions that look simple at the surface, but soon mire you down with needless work. Learn to identify these traps, and craft better solutions for the often-asked questions in this bo ...
The Art of Clean CodeMost software developers waste thousands of hours working with overly complex code. The eight core principles in The Art of Clean Code will teach you how to write clear, maintainable code without compromising functionality. The book's guiding principle is simplicity: reduce and simplify, then reinvest energy in the important parts to save you countless hours and ease the often onerous task of code maintenance.
Bestselling author Christian Mayer leverages his experience helping thousands perfect their coding skills in this new book.
This Python-based guide is suitable for programmers at any level, with ideas presented in a language-agnostic manner. ...
Practical Social EngineeringEven the most advanced security teams can do little to defend against an employee clicking a malicious link, opening an email attachment, or revealing sensitive information in a phone call. Practical Social Engineering will help you better understand the techniques behind these social engineering attacks and how to thwart cyber criminals and malicious actors who use them to take advantage of human nature.
Joe Gray, an award-winning expert on social engineering, shares case studies, best practices, open source intelligence (OSINT) tools, and templates for orchestrating and reporting attacks so companies can better protect themselves. He outlines creative techniques to trick users out of their credentials, such as leveraging Python scripts and editing HTML files to clone a legitimate website. Once you've succeeded in harvesting information about your targets with advanced OSINT methods, you'll discover how to defend your own organization from similar threats.
Fast-paced, hands-on, ...
3D Deep Learning with PythonWith this hands-on guide to 3D deep learning, developers working with 3D computer vision will be able to put their knowledge to work and get up and running in no time.
Complete with step-by-step explanations of essential concepts and practical examples, this book lets you explore and gain a thorough understanding of state-of-the-art 3D deep learning. You'll see how to use PyTorch3D for basic 3D mesh and point cloud data processing, including loading and saving ply and obj files, projecting 3D points into camera coordination using perspective camera models or orthographic camera models, rendering point clouds and meshes to images, and much more. As you implement some of the latest 3D deep learning algorithms, such as differential rendering, Nerf, synsin, and mesh RCNN, you'll realize how coding for these deep learning models becomes easier using the PyTorch3D library.
By the end of this deep learning book, you'll be ready to implement your own 3D deep learning models confidently. ...
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 3rd EditionThrough a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.
With this updated third edition, author Aurelien Geron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started. ...