Learn IT - Books tags inference

Think Stats

O'Reilly, 2011

If you know how to program, you have the skills to turn data into knowledge using the tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.

You'll work with a case study throughout the...

Markov Random Fields for Vision and Image Processing (MIT Press)

MIT Press, 2011

This volume demonstrates the power of the Markov random field (MRF) in vision, treating the MRF both as a tool for modeling image data and, utilizing recently developed algorithms, as a means of making inferences about images. These inferences concern underlying image and scene structure as well as solutions to such problems as image...

Programming Language Pragmatics, Second Edition

Morgan Kaufmann, 2005

"Michael Scott's book could have been entitled: Why Programming Languages Work. It takes a fresh look at programming languages by bringing together ideas and techniques usually covered in disparate language design, compiler, computer architecture, and operating system courses. Its comprehensive and integrated presentation of language...

Introducing Microsoft LINQ

Microsoft Press, 2007

Your first look at building data-rich applications using Microsoft LINQ.

Get a head start using Microsoft Language Integrated Query (LINQ). Two experienced developers give you advanced insights and expert guidance for using this unified model for data access. You will learn how to write queries in your native programming...

Soft Computing for Recognition based on Biometrics (Studies in Computational Intelligence)

Springer, 2010

We describe in this book, bio-inspired models and applications of hybrid intelligent systems using soft computing techniques for image analysis and pattern recognition based on biometrics and other information sources. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks,...

Programming Language Concepts (Undergraduate Topics in Computer Science)

Springer, 2012

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...

Statistics: Principles and Methods (Probability & Mathematical Statistics)

John Wiley & Sons, 1987

Covers all the basic concepts of statistics--descriptive study of data, probability, sampling variation, statistical inference, and special techniques for handling data--and illustrates them with practical examples that stimulate students' appreciation of the subject. Pays careful attention to the role of assumptions so that readers can...

Language and Automata Theory and Applications: 5th International Conference

Springer, 2012

These proceedings contain the papers that were presented at the 5th International Conference on Language and Automata Theory and Applications (LATA 2011), held in Tarragona, Spain, during May 26–31, 2011.

The scope of LATA is rather broad, including: algebraic language theory; algorithms for semi-structured...

Advances in Mathematical Modeling for Reliability

IOS Press, 2008

Advances in Mathematical Modeling for Reliability discusses fundamental issues on mathematical modeling in reliability theory and its applications. Beginning with an extensive discussion of graphical modeling and Bayesian networks, the focus shifts towards repairable systems: a discussion about how sensitive availability calculations parameter...

Functional Programming: A PragPub Anthology: Exploring Clojure, Elixir, Haskell, Scala, and Swift

Pragmatic Bookshelf, 2017

Explore functional programming and discover new ways of thinking about code. You know you need to master functional programming, but learning one functional language is only the start. In this book, through articles drawn from PragPub magazine and articles written specifically for this book, you'll explore functional...

Mathematics of Fuzzy Sets and Fuzzy Logic (Studies in Fuzziness and Soft Computing)

Springer, 2012

This book presents a mathematically-based introduction into the fascinating topic of Fuzzy Sets and Fuzzy Logic and might be used as textbook at both undergraduate and graduate levels and also as reference guide for mathematician, scientists or engineers who would like to get an insight into Fuzzy Logic.

Fuzzy Sets have been...

Hands-On Markov Models with Python: Implement probabilistic models for learning complex data sequences using the Python ecosystem

Packt Publishing, 2018

Unleash the power of unsupervised machine learning in Hidden Markov Models using TensorFlow, pgmpy, and hmmlearn

Key Features

Build a variety of Hidden Markov Models (HMM)

Create and apply models to any sequence of data to analyze, predict, and extract valuable...

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