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Approximation Methods for Efficient Learning of Bayesian Networks: Volume 168 Frontiers in Artificial Intelligence and Applications
Approximation Methods for Efficient Learning of Bayesian Networks: Volume 168 Frontiers in Artificial Intelligence and Applications

This publication offers and investigates efficient Monte Carlo simulation methods in order to realize a Bayesian approach to approximate learning of Bayesian networks from both complete and incomplete data. For large amounts of incomplete data when Monte Carlo methods are inefficient, approximations are implemented, such that learning remains...

AI Game Programming Wisdom 4 (AI Game Programming Wisdom (W/CD))
AI Game Programming Wisdom 4 (AI Game Programming Wisdom (W/CD))

Welcome to the latest volume of AI Game Programming Wisdom! AI Game Programming Wisdom 4 includes a collection of more than 50 new articles featuring cutting-edge techniques, algorithms, and architectures written by industry professionals for use in commercial game development. Organized into 7 sections, this comprehensive volume explores...

Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)
Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)
This book is intended to have three roles and to serve three associated audiences: an introductory text on Bayesian inference star ting from first principles, a graduate text on effective current approaches to Bayesian modeling and computation in statistics and related fields, and a handbook of Bayesian meth ods in applied...
Ruby Cookbook
Ruby Cookbook
Do you want to push Ruby to its limits? The Ruby Cookbook
is the most comprehensive problem-solving guide to today's hottest
programming
language. It gives you hundreds of solutions to real-world problems,
with clear explanations and thousands of lines of code you can use in
your own
...
Statistical Bioinformatics: with R
Statistical Bioinformatics: with R

Bioinformatics is an emerging field in which statistical and computational techniques are used extensively to analyze and interpret biological data obtained from high-throughput genomic technologies. Genomic technologies allow us to monitor thousands of biological processes going on inside living organisms in one snapshot, and are...

R Deep Learning Essentials
R Deep Learning Essentials

Key Features

  • Harness the ability to build algorithms for unsupervised data using deep learning concepts with R
  • Master the common problems faced such as overfitting of data, anomalous datasets, image recognition, and performance tuning while building the models
  • Build models relating to neural...
Probability: With Applications and R
Probability: With Applications and R

An introduction to probability at the undergraduate level

Chance and randomness are encountered on a daily basis. Authored by a highly qualified professor in the field, Probability: With Applications and R delves into the theories and applications essential to obtaining a thorough understanding of probability.

...
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis (Information Science and Statistics)
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis (Information Science and Statistics)
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification, troubleshooting, and data mining under uncertainty....
The Mobile MBA: 112 Skills to Take You Further, Faster
The Mobile MBA: 112 Skills to Take You Further, Faster

An MBA is a curious beast: it can accelerate your career, even if it has limited

practical value in day-to-day management.

Top employers hire top MBAs, but not because MBAs have mastered the mysteries of management. An MBA is a hallmark of personal commitment, effort, and ambition which
...
Mastering Machine Learning Algorithms: Expert techniques to implement popular machine learning algorithms and fine-tune your models
Mastering Machine Learning Algorithms: Expert techniques to implement popular machine learning algorithms and fine-tune your models

Explore and master the most important algorithms for solving complex machine learning problems.

Key Features

  • Discover high-performing machine learning algorithms and understand how they work in depth
  • One-stop solution to mastering supervised, unsupervised, and...
Machine Learning with R - Second Edition
Machine Learning with R - Second Edition

Key Features

  • Harness the power of R for statistical computing and data science
  • Explore, forecast, and classify data with R
  • Use R to apply common machine learning algorithms to real-world scenarios

Book Description

Machine learning, at its core, is concerned...

Enhanced Bayesian Network Models for Spatial Time Series Prediction: Recent Research Trend in Data-Driven Predictive Analytics (Studies in Computational Intelligence)
Enhanced Bayesian Network Models for Spatial Time Series Prediction: Recent Research Trend in Data-Driven Predictive Analytics (Studies in Computational Intelligence)
This research monograph is highly contextual in the present era of spatial/spatio-temporal data explosion. The overall text contains many interesting results that are worth applying in practice, while it is also a source of intriguing and motivating questions for advanced research on spatial data science. 

The
...
unlimited object storage image
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