DIGIRENT - Mastering Probabilistic Graphical Models using Python






[PDF.jg14] DIGIRENT - Mastering Probabilistic Graphical Models using Python
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 | #753956 in Books |  2015-08-03 |  2015-08-03 | Original language:English | PDF # 1 |  9.25 x.64 x7.50l,1.08 | File type: PDF | 287 pages

||0 of 0 people found the following review helpful.| Lots of Programming Errors|By Dr. Charles Saunders|If you are an inexperienced programmer or new to Python/Jupyter/Anaconda DO NOT BUY THIS OR ANY OTHER PACKT Publishing book as the code contains errors that are difficult to rectify. Packt Publishing DOES NOT verify code like the CRC Press - for instance, Bayesian Networks in R by CRC press - i.e. Probabilistic Graphical Model|About the Author||Ankur Ankan |Ankur Ankan is a BTech graduate from IIT (BHU), Varanasi. He is currently working in the field of data science. He is an open source enthusiast and his major work includes starting pgmpy with four other members. In his free

Master probabilistic graphical models by learning through real-world problems and illustrative code examples in Python

About This Book

  • Gain in-depth knowledge of Probabilistic Graphical Models
  • Model time-series problems using Dynamic Bayesian Networks
  • A practical guide to help you apply PGMs to real-world problems

Who This Book Is For

If you are a researcher or a machine learning enthusiast, or are working...



You easily download any file type for your gadget.Mastering Probabilistic Graphical Models using Python   |  Ankur Ankan, Abinash Panda. I was recommended this book by a dear friend of mine.

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