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Fundamentals of Data Science Trilogy: Experiment-Model-Learn

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Description

In this series, we cover statistical experimentation, modeling, and machine learning, focusing on: basic statistics, hypothesis testing, and experimentation validation methodology linear and logistic regression; generalized linear models causality time series analysis Bayesian statistics clustering decision trees, random forests, and boosted forests artificial neural networks and deep learning reinforcement learning Our focus is on mathematical derivations, algorithmic development, and programming. We use Python throughout the text to support our theory. All machine learning techniques are coded from scratch using Python.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
29 April 2022
Listed Since
06 April 2022

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