Shmueli G., Bruce P.C., Stephens M.L., Anandamurthy M., Peter C. Machine Learning for Business Analytics: Concepts, Techniques and Applications with JMP Pro

Nd Edition. — Wiley, 2023. — 611 p. — ISBN: 978-1119903831.An up-to-date introduction to a market-leading platform for data analysis and machine learning. Machine Learning for Business Analytics: Concepts, Techniques, and Applications with JMP Pro, 2nd ed. offers an accessible and engaging introduction to machine learning. It provides concrete examples and case studies to educate new users and deepen existing users’ understanding of their data and their business.PRELIMINARIES.Overview of the Machine Learning Process.
DATA EXPLORATION AND DIMENSION REDUCTION.
Data Visualization.
Dimension Reduction.
PERFORMANCE EVALUATION.
Evaluating Predictive Performance.
V PREDICTION AND CLASSIFICATION METHODS.
Multiple Linear Regression.
k-Nearest Neighbors (k-NN).
The Naive Bayes Classifier.
Classification and Regression Trees.
Logistic Regression.
Neural Nets.
Discriminant Analysis.
Generating, Comparing, and Combining Multiple Models.
INTERVENTION AND USER FEEDBACK.
Interventions: Experiments, Uplift Models, and Reinforcement Learning.
MINING RELATIONSHIPS AMONG RECORDS.
Association Rules and Collaborative Filtering.
Cluster Analysis.
FORECASTING TIME SERIES.
Handling Time Series.
Regression-Based Forecasting.
Smoothing and Deep Learning Methods for Forecasting.
DATA ANALYTICS.
Text Mining.
Responsible Data Science.
CASES.
Cases.