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Programming Bayesian Network Solutions with Netica
QAR 237
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Programming Bayesian Network Solutions with Netica provides a gentle but comprehensive introduction to programming Bayesian networks in Java with the Netica API.
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What Stands Out
Product Details
| Publisher | Lulu.com |
| Publication date | April 7, 2014 |
| Edition | Illustrated |
| Language | English |
| Print length | 206 pages |
| ISBN-10 | 1291812679 |
| ISBN-13 | 978-1291812671 |
| Item Weight | 2.31 pounds (1.05 kg) |
| Reading age | 1 year and up |
| Dimensions | 8.27 x 0.44 x 11.69 inches (21 x 1.1 x 29.7 cm) |
Who Should Buy?
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Data Scientists
Data scientists can leverage Netica for probabilistic modeling and analysis in complex datasets to make informed decisions.
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Research Analysts
Perfect for research analysts who require tools for statistical modeling and predictions based on uncertain data.
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Decision Makers
Decision-makers can use Netica to visualize and assess risks in uncertain environments before making critical choices.
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Casual Users
Not suitable for casual users who seek simple solutions without needing to understand Bayesian networks in depth.
Product Description
Programming Bayesian Network Solutions with Netica
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Programming Editorial Review
This illustrated edition of 'Programming Bayesian Network Solutions with Netica' provides a comprehensive guide to understanding and implementing Bayesian networks. The book covers the basics of probability theory and explores how to use Netica, a popular Bayesian network software, to build and analyze these networks. With clear explanations and numerous examples, this book is a valuable resource for anyone interested in Bayesian networks programming.
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Pros
- Comprehensive guide to understanding and implementing Bayesian networks
- Clear explanations and numerous examples
- Covers both probability theory and Netica software
Cons
- May be too technical for beginners
Product Price History
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QAR 237
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Features & Benefits
- Gentle and comprehensive introduction to programming Bayesian networks
- Written in Java with the Netica API
- Assumes minimal programming experience
- Suitable for those with basic understanding of Bayesian networks
- Ideal for creating software from small scripts to large projects
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