Supervised and unsupervised learning for data science. (2020)

• Record Type: Book
• Further Information: Note: Michael W. Berry, Azlinah Mohamed, Bee Wah Yap.
• Other Names: Berry, Michael W; Mohamed, Azlinah Hj; Wah, Yap Bee
• Contents: Chapter1: A Systematic Review on Supervised & Unsupervised Machine Learning Algorithms for Data Science -- Chapter2: Overview of One-Pass and Discard-After-Learn Concepts for Classification and Clustering in Streaming Environment with Constraints -- Chapter3: Distributed Single-Source Shortest Path Algorithms with Two Dimensional Graph Layout -- Chapter4: Using Non-Negative Tensor Decomposition for Unsupervised Textual Influence Modeling -- Chapter5: Survival Support Vector Machines: A Simulation Study and Its Health-related Application -- Chapter6: Semantic Unsupervised Learning for Word Sense Disambiguation -- Chapter7: Enhanced Tweet Hybrid Recommender System using Unsupervised Topic Modeling and Matrix Factorization based Neural Network -- Chapter8: New Applications of a Supervised Computational Intelligence (CI) Approach: Case Study in Civil Engineering.
• Publisher Details: Cham : Springer
• Publication Date: 2020
• Extent: 1 online resource (191 pages)
• Subjects: 006.31; Machine learning; Supervised learning (Machine learning); Machine learning; Supervised learning (Machine learning); Electronic books
• Languages: English
• ISBNs: 9783030224752; 3030224759
• Related ISBNs: 3030224740; 9783030224745
• Notes: Note: Includes bibliographical references and index.; Note: Print version record.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.