56891Pro android 3
Pro android 3 shows we how to build real-world and fun mobile applications using the new android 3.0 SDK. It covers everything from the fundamentals of building apps for embedded devices, phones, and tablets to advanced concepts such as custom 3D components and multi-tasking.
56892Pro node.js for developers
Introducing Node.js The Node Module System The Event Loop Events Timers and Scheduling The Command Line Interface Accessing the File System Data Streams Binary Data Creating Child Processes Network Programming HTTP Server Development Connect Connecting to Databases Logging.
56893Pro unity game development with C#
It presents ten chapters such as designing and preparing, getting started, event handling, power-úp and singletons, player controller, weapons, enemies,...
56894Pro Web 2.0 Mashups: Remixing data and web services
Mashups are hugely popular right now, a very important topic within the general area of Web 2.0, involving technologies such as CSS, JavaScript, Ajax, APIs, libraries, and server-side languages (such as PHP and ASP.NET.) This book aims to be the definitive tome on Mashup development, to stand in the middle of all the other, more API specific books coming out on Google Maps, Flickr, etc. The book shows how to create real world Mashups using all the most poplar APIs, such as Google Maps, Flickr, Amazon Web Services, and delicious, and includes examples in multiple different server-side languages, such as PHP, Java, and .NET.
56895Probabilistic machine learning : advanced topics
An advanced counterpart to Probabilistic Machine Learning: An Introduction, this high-level textbook provides researchers and graduate students detailed coverage of cutting-edge topics in machine learning, including deep generative modeling, graphical models, Bayesian inference, reinforcement learning, and causality. This volume puts deep learning into a larger statistical context and unifies approaches based on deep learning with ones based on probabilistic modeling and inference. With contributions from top scientists and domain experts from places such as Google, DeepMind, Amazon, Purdue University, NYU, and the University of Washington, this rigorous book is essential to understanding the vital issues in machine learning.
56896Probabilistic methods of signal and system analysis
Introduction to probability, random variables, several random variables, elements of statistics, random processes, correlation functions, spectral density, response of linear systems to random inputs, optimum linear systems.
56897Probabilistic methods of signal and system analysis : 3rd ed.
Introduction to probability; Random varibles; Several random variables; Elements of statistics; random processes; Correlation functions; Spectral density; Response of linear systems to random inputs.
56898Probabilistic methods of signal and system analysis : 3rd ed.
1. Introduction to probability; 2. Random variables; 3. Several random variables; 4. Elements of statistics; 5. Random processes; 6. Correlation functions; 7. Spectral density; 8. Response of linear systems to random inputs; 9. Optimum linear systems.
56899Probabilistic methods of signal and system analysis : 3rd ed.
Introduction to probability; Random variables; Several random variables; Elements of statistics; Random processes; Correlation function; Spectral density; Response of linear systems to random inputs.
56900Probability and measure : anniversary edition
Probability and Measure, Anniversary Edition by Patrick Billingsley celebrates the achievements and advancements that have made this book a classic in its field for the past 35 years. Now re-issued in a new style and format, but with the reliable content that the third edition was revered for, this Anniversary Edition builds on its strong foundation of measure theory and probability with Billingsley's unique writing style. In recognition of 35 years of publication, impacting tens of thousands of readers, this Anniversary Edition has been completely redesigned in a new, open and user-friendly way in order to appeal to university-level students.