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This book introduces machine learning and deep learning concepts and algorithms applied to a diverse set of behavior analysis problems. It focuses on the practical aspects of solving such problems based on data collected from sensors or stored in electronic records.
Enrique is a Data Scientist at Optimeering. He was previously a Researcher at SINTEF, Norway. He also worked as a PostDoc at the University of Oslo. For the last 11 years, he has been conducting research on behavior analysis using machine learning. Feel free to contact him for any questions, comments, and feedback. e-mail: e.g.mx [at] ieee.org twitter: https://twitter.com/e_g_mx website: http://www.enriquegc.com
1. Introduction to Behavior and Machine Learning 2. Predicting Behavior with Classification Models 3. Predicting Behavior with Ensemble Learning 4. Exploring and Visualizing Behavioral Data 5. Preprocessing Behavioral Data 6. Discovering Behaviors with Unsupervised Learning 7. Encoding Behavioral Data 8. Predicting Behavior with Deep Learning 9. Multi-User Validation 10. Detecting Abnormal Behaviors Appendix A. Setup Your Environment Appendix B. Datasets