📚 Books related to data

Here you can find books mostly shared by the Universidad Nacional de Cordoba for a data science extension course.

Some other books are by my own as a recommendation about alghorithms, philosophical point of view about technology, bussiness and so on.

Books's languages are mixed between spanish and english.

Statistics

• Anderson Sweeney Williams - Estadistica para Administracion y economia

A book with very good examples to understand complex concepts like linear regressions.

• Enders Wiley - Applied Econometric Time Series

• Gareth - An Introduction to Statistical Learning

An excellent starter book about statistical techniques in general and machine learning in particular. It guides you from traditional statistcal point of you to a newer way to understand the same problems. A python version of the code can be founded in https://github.com/JWarmenhoven/ISLR-python.

• Gujaraty & Porter -Econometria

A reference book for economists. Good material to understand Linear Regression. Often cited in different papers as a theoretical foundation.

• Analisis multivariante aplicado con R

• Guia practica dfe econometrica basica con python

Good practical examples about Linear Regression using stats model library from python.

• Tukey - Exploratory data analysis.

Another reference book. Could be oldy, but Tukey created the concept of EDA which consists in a serie of techniques to understand the composition of your data. For instance, box-and-whisker plot was first introduced in this book.

• Wooldridge - Introductory Econometrics

Machine Learning

• Introduction to machine learning with Python

• Jake Vander - Python Data Science handbook - 2017

• Johw w Foreman - Data smart using data science

This book was wrote by the CTO of Mailchimp. It has a very practical point of view to resolve mostly marketing data questions related to users and product. It uses Excel mostly to resolve those questions.

• Data mining with decision trees, theory and applications

• Sandro Skansi - Introduction to deep learning

• Python Machine learning - Sebastian Raschka

General

• The managers path

A practical guide to understanding and pursuing a career In Engineering Management

• Clyton - The innovators Dilemma

• You are not a gadget - Jaron Lanier

Jaron Lanier has another book called Who owns the future. He has a very interesting point of view about how tech drives our life.

Tech

• Andrew Tanenbaum - Distributed Systems

From the creator of a classical book called Modern Operating Systems

• Grokking Algorithms and illustrated guide

A very good resource to understand the most common algoruithms used in programming like buble sort and so on.

• Martin Kleppmann - Designing Data intesive applications

From my pov, one of the best books in the tech industry. It allows you to understand how index works, tradeoffs, queues, etc, all of that in a distributed scenario with very real problems/examples like twitter notifications problem for very popular and unpopular users.

Also it talks at the end of book about the concept of "unbundling" a database.

-Practical cryptography in python

The best practical and theorical introduction that I found about cryptography. SSL Certificates don't will be a problem anymore after this book.

List made between 2021/2022.