Learn IT - Books tags markov

Scala Machine Learning Projects: Build real-world machine learning and deep learning projects with Scala

Packt Publishing, 2018

Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming.

Key Features

Explore machine learning techniques with prominent open source Scala libraries such as Spark ML, H2O, MXNet, Zeppelin, and DeepLearning4j

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Domain-Specific Languages in R: Advanced Statistical Programming

Apress, 2018

Gain an accelerated introduction to domain-specific languages in R, including coverage of regular expressions. This compact, in-depth book shows you how DSLs are programming languages specialized for a particular purpose, as opposed to general purpose programming languages. Along the way, you’ll learn to specify tasks...

Bayesian Logical Data Analysis for the Physical Sciences: A Comparative Approach with Mathematica® Support

Cambridge University Press, 2010

Bayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. By incorporating relevant prior information, it can sometimes improve model parameter estimates by many orders of magnitude. This book...

Tools and Algorithms for the Construction and Analysis of Systems (Lecture Notes in Computer Science)

Springer, 2007

ETAPS 2007 is the tenth instance of the European Joint Conferences on Theory and Practice of Software, and thus a cause for celebration.

The events that comprise ETAPS address various aspects of the system development process, including specification, design, implementation, analysis and...

Applied Bayesian Statistics: With R and OpenBUGS Examples (Springer Texts in Statistics)

Springer, 2013

This book is based on over a dozen years teaching a Bayesian Statistics course. The material presented here has been used by students of different levels and disciplines, including advanced undergraduates studying Mathematics and Statistics and students in graduate programs in Statistics, Biostatistics, Engineering, Economics,...

Probability and Algorithms

National Academy Press, 1992

Some of the hardest computational problems have been successfully attacked through the use of probabilistic algorithms, which have an element of randomness to them. Concepts from the field of probability are also increasingly useful in analyzing the performance of algorithms, broadening our understanding beyond that provided by the...

GARCH Models: Structure, Statistical Inference and Financial Applications

John Wiley & Sons, 2019

Provides a comprehensive and updated study of GARCH models and their applications in finance, covering new developments in the discipline

This book provides a comprehensive and systematic approach to understanding GARCH time series models and their applications whilst presenting the most advanced results...

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