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Fundamentals of Machine Learning for Predictive Data Analytics
Algorithms, Worked Examples, and Case Studies
Langbeschreibung
The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice.
Inhaltsverzeichnis
I Introduction to Machine Learning and Data Analytics 1 Machine Learning for Predictive Data Analytics 2 Data to Insights to Decisions 3 Data Exploration II Predictive Data Analytics 4 Information-Based Learning 5 Similarity-Based Learning 6 Probability-Based Learning 7 Error-Based Learning 8 Deep Learning 9 Evaluation III Beyond Prediction 10 Beyond Prediction: Unsupervised Learning 11 Beyond Prediction: Reinforcement Learning IV Case Studies and Conclusions 12 Case Study: Customer Churn 13 Case Study: Galaxy Classification 14 The Art of Machine Learning for Predictive Data Analytics V Appendices A Descriptive Statistics and Data Visualization for Machine Learning B Introduction to Probability for Machine Learning C Differentiation Techniques for Machine Learning D Introduction to Linear Algebra Bibliography Index
John D. Kelleher, Brian Mac Namee, and Aoife D'Arcy
ISBN-13:
9780262044691
Veröffentl:
2020
Erscheinungsdatum:
20.10.2020
Seiten:
798
Autor:
John D. Kelleher
Gewicht:
1445 g
Format:
244x203x38 mm
Sprache:
Englisch