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Introduction.- Supervised and unsupervised methods for customer segmentation.- Supervised and unsupervised methods for supply chain management.- Supervised and unsupervised methods for logistics improvement.- Design of recommender systems.- Supervised and unsupervised methods for e-marketing.- Analysis of Blockchain data.- Supervised and unsupervised methods applied in banking.- Cryptocurrency analysis.- Supervised and unsupervised methods to improve operational processes.- Big data analysis and summarization.- Intelligent Financial analysis and sales forecasting.- Financial data modeling and decision making.- Integration of learning methods in Smart ERP systems.- E-commerce recommender systems.- Social media and E-business analysis.- Intelligent Business control and monitoring systems.- Conclusion.
Title: Machine Learning and Data Analytics for ...
Publisher: Springer
Publication Date: 2022
Binding: Soft cover
Condition: New