By using concrete examples, minimal theory, and two production-ready Python frameworks - scikit-learn and TensorFlow - author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems.
This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.
This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.
