Machine learning with SAS : special collection
Title By: Sethi, Saratendu [forwarded by]
Material type: BookDescription: 1 volume (various pagings) : illustrations ; 28 cm.ISBN: 9781642954760Subject(s): Business enterprises -- Evaluation -- Case studies | Machine learning | Business enterprises -- Evaluation | Machine learningDDC classification: 338.7 MA CH Online resources: EbookItem type | Home library | Call number | Status | Date due | Barcode | Item holds | Course reserves |
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eBook | University of Wollongong in Dubai eBook | 338.7 MA CH (Browse shelf) | Available | T0065344 |
Includes bibliographical references.
An Overview of SAS Visual Data Mining and Machine Learning on SAS Viya -- Interactive Modeling in SAS Visual Analytics -- Open Your Mind: Use Cases for SAS and Open-Source Analytics -- Automated Hyperparameter Tuning for Effective Machine Learning -- Random Forests with Approximate Bayesian Model Averaging -- Methods of Multinomial Classification using Support Vector Machines -- Factorization Machines: A New Tool for Sparse Data -- Building Bayesian Network Classifiers Using the HPBNET Procedure -- Stacked Ensemble Models for Improved Prediction Accuracy.
Machine learning is a branch of artificial intelligence (AI) that develops algorithms that allow computers to learn from examples without being explicitly programmed. Machine learning identifies patterns in the data and models the results. These descriptive models enable a better understanding of the underlying insights the data offers. Machine learning is a powerful tool with many applications, from real-time fraud detection, the Internet of Things (IoT), recommender systems, and smart cars. It will not be long before some form of machine learning is integrated into all machines, augmenting the user experience and automatically running many processes intelligently.