Bibliografia

"Hastie T, Tibshirani T, Friedman J, The elements of statistical Data-Mining, Inférence and prediction second edition. Springer-Verlag New York, (2009), 533p. ISBN : 978-0-387-84858-7 Artificial Intelligence in Healthcare: AI, Machine Learning, and Deep and Intelligent Medicine Simplified for Everyone (English Edition), Parag Mahajan P. Tattar, T. Ojeda, S. P. Murphy B. Bengfort, A. Dasgupta, Practical Data Science Cookbook, Second Edition. Packt Publishing. 2017 C. O'Neil, R. Schutt. Doing Data Science: Straight Talk from the Frontline. O'Reilly. 2013": - -

"""Python for Data Analysis"" by Wes McKinney - This book is a comprehensive guide to data analysis using Python, and covers topics such as data manipulation, visualization, and machine learning. ""Data Science from Scratch: First Principles with Python"" by Joel Grus - This book provides an introduction to data science using Python, and covers topics such as data cleaning, exploratory data analysis, and statistical inference. James G, Witten D, Hastie T, Tibshirani T, An introduction to statistical learning with applications in R. second edition. Springer-Verlag New York, (2021), 607p. ISBN : 978-1-0716-1418-1 Topol, E. J. (2019). Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books. P. Mathur, Machine Learning Applications Using Python: Cases Studies from Healthcare, Retail, and Finance. Apress. 2018.": - -