00000nam a22000004a 4500 UP-8027390931311820037 Buklod 20250415103754.0 m |o d | ta 250415s2024 ii a rb |001 0|eng d 9788119365630 (Hardback) BC-75663 Mind Mover Publishing House Inc. Php5080.00 Criselda Libatique/Department of Mathematics and Computer Science BAG rda eng Q 325.5 M33 2024 Machine learning and data mining editor, Carlton Braganza. New Delhi, India Discovery Publishing House [2024] 263 pages illustrations 25 cm text rdacontent unmediated rdamedia volume rdacarrier Includes bibliographical references and index. A survey of machine learning for big data processing / Junfei Qiu , Qihui Wu, Guoru Ding , Yuhua Xu, and Shuo Feng -- Machine learning applications in misuse and anomaly detection / Jaydip Sen and Sidra Mehtab -- An intelligent approach using machine learning techniques to predict flow in people / M.C. Pegalajar, L.G. B. Ruiz, E. Perez-Moreiras, J. Boada-Grau and M.J. Serrano-Fernandez -- Cybersecurity data science: an overview from machine learning perspective / Iqbal H. Sarker, A.S. M. Kayes, Shahriar Badsha , Hamed Alqahtani, Paul Watters and Alex Ng -- Review on reliable pattern recognition with machine learning / Devyani Bhamare and Poonam Suryawanshi -- One method of generating synthetic data to assess the upper limit of machine learning algortihms perfomance / Yan I. Kuchin, Ravil I. Mukhamediev and Kirill O. Yakunin -- Meta-map reduce for scalable data mining / Xuan Liu, Xiaoguang Wang, Stan Matwin and Nathalie Japkowicz -- Using machine learning to evaluate coal geochemical data with respect to dynamic failures / David R. Hanson and Heather E. Lawson -- Educational data mining: prediction of students' academic performance using machine learning algorithms / Mustafa Yagci -- Data analysis of quarry operations and maintenance schedules: a production optimization study / Brennan George and Bahareh Nojabaei -- Machine learning approach for predicting production delays: a quarry company case study / Rathimala Kannan, Haq'ul Aqif Abdul Halim, Kannan Ramakrishnan, Shahrinaz Ismail and Dedy Rahman Wijaya -- Best practices in accelerating the data science process in python / Deanne Larson. "The book 'Machine Learning and Data Mining' focuses on different classification techniques, such as decision trees, support vector machines, and nearest neighbors. It delves into methods like decision trees, support vector machines, and nearest neighbors. The book offers a comparative analysis of these algorithms, emphasizing their individual advantages and drawbacks. Its aim is to assist researchers, practitioners, and data scientists in selecting the most appropriate classification algorithm for their particular requirements. By providing insights into the different techniques, this comprehensive guide aids in the decision-making process when it comes to choosing the right approach for classification tasks. This comprehensive guide helps researchers, practitioners, and data scientists choose the most suitable classification algorithm for their specific needs." Machine learning. Data mining. Braganza, Carlton editor. FO UPBAG UPBAG-MAIN Q 325.5 M33 2024 Book