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This month we highlight these 3 books:
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This book is the simple and definitive guide to the Python 3 Object Oriented Programming. Other book of the similar genres make use of complicated writing style and examples to introduce the readers to the OOP in Python 3. However, this book uses Simple language to explain concepts. It is aimed at intermediate learners who already know Python.
This book takes us on a journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories – Bayesian, frequentist, Fisherian – individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The book integrates methodology and algorithms with statistical inference, and ends with speculation on the future direction of statistics and data science.
Trevor Hastie, Robert Tibshirani and Martin Wainwright
During the past decade there has been an explosion in computation and information technology. With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. This book descibes the important ideas in these areas in a common conceptual framework.
Related Udemy Video Courses
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