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Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference (Addison-Wesley Data & Analytics)
Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference (Addison-Wesley Data & Analytics)

Master Bayesian Inference through Practical Examples and Computation–Without Advanced Mathematical Analysis

 

Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely...

Python Machine Learning Cookbook
Python Machine Learning Cookbook

100 recipes that teach you how to perform various machine learning tasks in the real world

About This Book

  • Understand which algorithms to use in a given context with the help of this exciting recipe-based guide
  • Learn about perceptrons and see how they are used to build neural...
Exploring Monte Carlo Methods
Exploring Monte Carlo Methods

Exploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear...

Probability Theory: A Comprehensive Course (Universitext)
Probability Theory: A Comprehensive Course (Universitext)

This second edition of the popular textbook contains a comprehensive course in modern probability theory. Overall, probabilistic concepts play an increasingly important role in mathematics, physics, biology, financial engineering and computer science. They help us in understanding magnetism, amorphous media, genetic diversity and the perils...

Bioinformatics: The Machine Learning Approach, Second Edition (Adaptive Computation and Machine Learning)
Bioinformatics: The Machine Learning Approach, Second Edition (Adaptive Computation and Machine Learning)

We have been very pleased, beyond our expectations, with the reception of the first edition of this book. Bioinformatics, however, continues to evolve very rapidly, hence the need for a new edition. In the past three years, fullgenome sequencing has blossomed with the completion of the sequence of the fly and the first draft of the...

Mathematical Models of Spoken Language
Mathematical Models of Spoken Language
Humans use language to convey meaningful messages to each other. Linguistic competence consists in the ability to express meaning reliably, not simply to obtain faithful lexical transcriptions. This invaluable reference tool is the product of many years' experience and research on language and speech technology. It presents the motivations for,...
Markov Random Fields for Vision and Image Processing (MIT Press)
Markov Random Fields for Vision and Image Processing (MIT Press)

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...

Advances In Quantitative Analysis Of Finance And Accounting
Advances In Quantitative Analysis Of Finance And Accounting
Advances in Quantitative Analysis of Finance and Accounting is an annual publication designed to disseminate developments in the quantitative analysis of finance and accounting. The publication is a forum for statistical and quantitative analyses of issues in finance and accounting, as well as applications of quantitative methods to problems in...
Bioinformatics: High Performance Parallel Computer Architectures (Embedded Multi-Core Systems)
Bioinformatics: High Performance Parallel Computer Architectures (Embedded Multi-Core Systems)

New sequencing technologies have broken many experimental barriers to genome scale sequencing, leading to the extraction of huge quantities of sequence data. This expansion of biological databases established the need for new ways to harness and apply the astounding amount of available genomic information and convert it into substantive...

A First Course in Stochastic Models
A First Course in Stochastic Models
The teaching of appliedprobability needs a fresh approach. The fieldof applied probability has changedprofound ly in the past twenty years andyet the textbooks in use today do not fully reflect the changes. The development of computational methods has greatly contributed to a better understanding of the theory. It is my conviction that theory is...
Stochastic Modeling and Analysis of Telecoms Networks
Stochastic Modeling and Analysis of Telecoms Networks

This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.
The authors propose a
...

Data Algorithms: Recipes for Scaling Up with Hadoop and Spark
Data Algorithms: Recipes for Scaling Up with Hadoop and Spark

If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem, such as...

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