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£108.01
Springer - Dirty Data Processing for Machine Learning Book
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Description
Key Features
Analyzes the specific impacts that dirty data has on machine learning and data mining tasks.
Explores effective methods for processing dirty data to improve the accuracy of results.
Examines the relationship between data quality in training and test datasets.
Addresses the high costs associated with existing data cleaning methods.
Provides insights into how data quality issues affect machine learning accuracy.
Product Specifications
- Brand
- Springer
- Format
- paperback
- ASIN
- 9819976596
- Domain
- Amazon UK
- Release Date
- 01 December 2024
- Listed Since
- 03 December 2024
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