{
"item_title" : "Machine Learning in Industry",
"item_author" : [" Shubhabrata Datta", "J. Paulo Davim "],
"item_description" : "This book covers different machine learning techniques such as artificial neural network, support vector machine, rough set theory and deep learning. It points out the difference between the techniques and their suitability for specific applications. This book also describes different applications of machine learning techniques for industrial problems. The book includes several case studies, helping researchers in academia and industries aspiring to use machine learning for solving practical industrial problems.",
"item_img_path" : "https://covers2.booksamillion.com/covers/bam/3/03/075/849/3030758494_b.jpg",
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Overview
This book covers different machine learning techniques such as artificial neural network, support vector machine, rough set theory and deep learning. It points out the difference between the techniques and their suitability for specific applications. This book also describes different applications of machine learning techniques for industrial problems. The book includes several case studies, helping researchers in academia and industries aspiring to use machine learning for solving practical industrial problems.
This item is Non-Returnable
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Details
- ISBN-13: 9783030758493
- ISBN-10: 3030758494
- Publisher: Springer
- Publish Date: July 2022
- Dimensions: 9.21 x 6.14 x 0.44 inches
- Shipping Weight: 0.66 pounds
- Page Count: 197
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