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You're reading from  Learning Bayesian Models with R

Product typeBook
Published inOct 2015
Reading LevelBeginner
PublisherPackt
ISBN-139781783987603
Edition1st Edition
Languages
R
Concepts
Machine Learning
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Author (1)
Hari Manassery Koduvely
Hari Manassery Koduvely
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Hari Manassery Koduvely

Dr. Hari M. Koduvely is an experienced data scientist working at the Samsung R&D Institute in Bangalore, India. He has a PhD in statistical physics from the Tata Institute of Fundamental Research, Mumbai, India, and post-doctoral experience from the Weizmann Institute, Israel, and Georgia Tech, USA. Prior to joining Samsung, the author has worked for Amazon and Infosys Technologies, developing machine learning-based applications for their products and platforms. He also has several publications on Bayesian inference and its applications in areas such as recommendation systems and predictive health monitoring. His current interest is in developing large-scale machine learning methods, particularly for natural language understanding.
Read more about Hari Manassery Koduvely

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References

  1. Matloff N. The Art of R Programming – A Tour of Statistical Software Design. No Starch Press. 2011. ISBN-10: 1593273843

  2. Teetor P. R Cookbook. O'Reilly Media. 2011. ISBN-10: 0596809158

  3. Wickham H. Advanced R. Chapman & Hall/CRC The R Series. 2015. ISBN-10: 1466586966

  4. Wickham H. ggplot2: Elegant Graphics for Data Analysis (Use R!). Springer. 2010. ISBN-10: 0387981403

  5. Auto MPG Data Set, UCI Machine Learning repository, https://archive.ics.uci.edu/ml/datasets/Auto+MPG

  6. Quinlan R. "Combining Instance-Based and Model-Based Learning". In: Tenth International Conference of Machine Learning. 236-243. University of Massachusetts, Amherst. Morgan Kaufmann. 1993

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Learning Bayesian Models with R
Published in: Oct 2015Publisher: PacktISBN-13: 9781783987603
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Author (1)

author image
Hari Manassery Koduvely

Dr. Hari M. Koduvely is an experienced data scientist working at the Samsung R&D Institute in Bangalore, India. He has a PhD in statistical physics from the Tata Institute of Fundamental Research, Mumbai, India, and post-doctoral experience from the Weizmann Institute, Israel, and Georgia Tech, USA. Prior to joining Samsung, the author has worked for Amazon and Infosys Technologies, developing machine learning-based applications for their products and platforms. He also has several publications on Bayesian inference and its applications in areas such as recommendation systems and predictive health monitoring. His current interest is in developing large-scale machine learning methods, particularly for natural language understanding.
Read more about Hari Manassery Koduvely

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