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Machine Learning Algorithms for Industrial Applications

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Cover of 'Machine Learning Algorithms for Industrial Applications'

Table of Contents

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    Book Overview
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    Chapter 1 A Hybrid Feature Selection Approach Based on LSI for Classification of Urdu Text
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    Chapter 2 Automated Document Categorization Model
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    Chapter 3 Automated Categorization and Mining Tweets for Disaster Management
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    Chapter 4 Sentiment Analysis in Airline Data: Customer Rating Based Recommendation Prediction Using WEKA
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    Chapter 5 Image Inpainting for Irregular Holes Using Extreme Learning Machine
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    Chapter 6 OCR Using Computer Vision and Machine Learning
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    Chapter 7 Few Shot Learning for Medical Imaging
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    Chapter 8 Hyperspectral Remote Sensing Image Classification Using Active Learning
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    Chapter 9 A Smart Document Converter: Conversion of Handwritten Text Document to Computerized Text Document
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    Chapter 10 GRNN Based an Intelligent Technique for Image Inpainting
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    Chapter 11 Content-Based Airline Recommendation Prediction Using Machine Learning Techniques
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    Chapter 12 A Meta-heuristic Based Approach for Slope Stability Analysis to Design an Optimal Soil Slope
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    Chapter 13 An Application of Operational Analytics: For Predicting Sales Revenue of Restaurant
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    Chapter 14 Application of Machine Learning Algorithm for Anomaly Detection for Industrial Pumps
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    Chapter 15 Fast Accessing Non-volatile, High Performance-High Density, Optimized Array for Machine Learning Processor
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    Chapter 16 Long Term Evolution for Secured Smart Railway Communications Using Internet of Things
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    Chapter 17 Application of Flower Pollination Algorithm to Locate Critical Failure Surface for Slope Stability Analysis
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Title
Machine Learning Algorithms for Industrial Applications
Published by
Springer International Publishing, January 2021
DOI 10.1007/978-3-030-50641-4
ISBNs
978-3-03-050640-7, 978-3-03-050641-4
Editors

Santosh Kumar Das, Shom Prasad Das, Nilanjan Dey, Aboul-Ella Hassanien

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