The expert guide to creating production machine learning solutions with ML.NET! ML.NET brings the power of machine learning to all .NET developers— and Programming ML.NET helps you apply it in real production solutions. Modeled on Dino Esposito's best-selling Programming ASP.NET, this book takes the same scenario-based approach Microsoft's team used to build ML.NET itself. After a foundational overview of ML.NET's libraries, the authors illuminate mini-frameworks (“ML Tasks”) for regression, classification, ranking, anomaly detection, and more. For each ML Task, they offer insights for overcoming common real-world challenges. Finally, going far beyond shallow learning, the authors thoroughly introduce ML.NET neural networking. They present a complete example application demonstrating advanced Microsoft Azure cognitive services and a handmade custom Keras network— showing how to leverage popular Python tools within .NET. 14-time Microsoft MVP Dino Esposito and son Francesco Esposito show how to: Build smarter machine learning solutions that are closer to your user's needs See how ML.NET instantiates the classic ML pipeline, and simplifies common scenarios such as sentiment analysis, fraud detection, and price prediction Implement data processing and training, and “productionize” machine learning–based software solutions Move from basic prediction to more complex tasks, including categorization, anomaly detection, recommendations, and image classification Perform both binary and multiclass classification Use clustering and unsupervised learning to organize data into homogeneous groups Spot outliers to detect suspicious behavior, fraud, failing equipment, or other issues Make the most of ML.NET's powerful, flexible forecasting capabilities Implement the related functions of ranking, recommendation, and collaborative filtering Quickly build image classification solutions with ML.NET transfer learning Move to deep learning when standard algorithms and shallow learning aren't enough “Buy” neural networking via the Azure Cognitive Services API, or explore building your own with Keras and TensorFlow

Java Network Programming, Third Edition, brings you up-to-date with the latest features of Java's network APIS. This book discusses all the changes and additions to networking in JDK 1.4 and 1.5 (now christened J2SE 5). It covers everything from networking fundamentals to remote method invocation (RMI), including chapters on TCP and UDP sockets, server sockets, URLs and URIs, multicasting, and special-purpose APIS such as JavaMail. This book shows you how to use JSSE to write secure networking applications and explains how to use the NIO APIs to write ultra high-performance servers. And it covers Java's support for network proxies, web cookies, and URL caching. Java Network Programming doesn't just explain the APIS: it shows you how to put them to work. This book is full of examples; it contains thousands of lines of working code (all of which are available online), implementing fully functional network clients and servers. Whether you want to write a special-purpose web server, a secure online order taker, a simple multicast agent, or even an email client, you'll find code that you can learn from and borrow. Whether you're an experienced network developer, a new Java programmer, or someone who just wants to see what's possible, you'll find that Java Network Programming, Third Edition is an important part of your library. Once you've started using the Java Networking APIs, the possibilities are only limited by your imagination.

* Pro ASP.NET 2.0 Website Programming shows how to provide users and customers with ASP.NET 2.0 websites that are easy-to-use, perform well, and secure. * This book clearly explains how to handle all of the common website tasks effortlessly: including logging in, displaying important customer information, querying data, reporting. and security. * With this book, readers will learn ASP.NET 2.0 and how to apply it to solve real business problems.

Programming Language Concepts uses a functional programming language (F#) as the metalanguage in which to present all concepts and examples, and thus has an operational flavour, enabling practical experiments and exercises. It includes basic concepts such as abstract syntax, interpretation, stack machines, compilation, type checking, and garbage collection techniques, as well as the more advanced topics on polymorphic types, type inference using unification, co- and contravariant types, continuations, and backwards code generation with on-the-fly peephole optimization. Programming Language Concepts covers practical construction of lexers and parsers, but not regular expressions, automata and grammars, which are well covered elsewhere. It throws light on the design and technology of Java and C# to strengthen students’ understanding of these widely used languages. The examples present several interpreters and compilers for toy languages, including a compiler for a small but usable subset of C, several abstract machines, a garbage collector, and ML-style polymorphic type inference. Each chapter has exercises based on such examples.