Bayesian Networks: With Examples in r [Audiobook] download free by Marco Scutari

Bayesian Networks: With Examples in r Audiobook download free by Marco Scutari
  • Listen audiobook: Bayesian Networks: With Examples in r
  • Author: Marco Scutari
  • Release date: 2014/12/5
  • Language: English
  • Genre or Collection: Computing
  • ISBN: 9781482225587
  • Rating: 9.85 of 10
  • Votes: 135
  • Review by: Scarlet Saavedra
  • Review rating: 7.38 of 10
  • Review Date: 2018/10/21
  • Duration: 3H4M38S in 256 kbps (48.2 MB)
  • Date of creation of the audiobook: 2018-08-14
  • You can listen to this audiobook in formats: FLAC, AIFF, MPEG4, WAV, WMA, MP3, AU (compression RAR, BZ2, ZIP, TAR.7Z, CPIO, 7Z, TZ)
  • Total pages original book: 241
  • Includes a PDF summary of 24 pages
  • Duration of the summary (audio): 18M8S (4.8 MB)
  • Description or summary of the audiobook: Understand the Foundations of Bayesian Networks-Core Properties and Definitions Explained Bayesian Networks: With Examples in R introduces Bayesian networks using a hands-on approach. Simple yet meaningful examples in R illustrate each step of the modeling process. The examples start from the simplest notions and gradually increase in complexity. The authors also distinguish the probabilistic models from their estimation with data sets.The first three chapters explain the whole process of Bayesian network modeling, from structure learning to parameter learning to inference. These chapters cover discrete Bayesian, Gaussian Bayesian, and hybrid networks, including arbitrary random variables.The book then gives a concise but rigorous treatment of the fundamentals of Bayesian networks and offers an introduction to causal Bayesian networks. It also presents an overview of R and other software packages appropriate for Bayesian networks. The final chapter evaluates two real-world examples: a landmark causal protein signaling network paper and graphical modeling approaches for predicting the composition of different body parts.Suitable for graduate students and non-statisticians, this text provides an introductory overview of Bayesian networks. It gives readers a clear, practical understanding of the general approach and steps involved.
  • Other categories, genre or collection: Biology, Life Sciences, Computer Science, Probability & Statistics
  • Download servers: UsersCloud, Torrent, Mediafire, FileServe, 4Shared. Compressed in RAR, BZ2, ZIP, TAR.7Z, CPIO, 7Z, TZ
  • Format: Hardback
  • Approximate value: 99.77 USD
  • Dimensions: 156x235x20.32mm
  • Weight: 476g
  • Printed by: Not Available
  • Published in: Oakville, Canada

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