5.0 out of 5 stars Concise overview of Data Science and its applications

S. · 27 January 2020

(function() { P.when('cr-A', 'ready').execute(function(A) { if(typeof A.toggleExpanderAriaLabel === 'function') { A.toggleExpanderAriaLabel('review_text_read_more', 'Read more of this review', 'Read less of this review'); } }); })(); .review-text-read-more-expander:focus-visible { outline: 2px solid #2162a1; outline-offset: 2px; border-radius: 5px; } I found this book to be an excellent way of familiarising myself with Data Science, coming from a non-Computer Science (Economics) background.It covers the recent literature on such computational methods from, the current applications and the challenges behind Data Science. The book also talks about the various types of data along with the use cases like nominal/ordinal (categorical) and numeric data. Eventually, getting to what I think is the best chapter in the book is 'Machine Learning 101', which easily explains the types of what's the difference between supervised learning (classification/regression problems) and unsupervised learning (clustering, segmentation etc.). Only Maths (Algebra/statistics) up to high school/college level is needed to understand the principles of how most of the algorithms are set-up.The only thing I think this book was disappointing at was the explanation of Deep Learning, which I feel was slightly brushed over compared to Machine Learning, when in some way, Deep Learning may have deserved its own chapter.Finally, the book ended on the legislation side of Data Ethics, such as GDPR and the trade-off between accurate analysis and privacy among users of the internet/digital applications, again illustrating the future path for Data Science.I would recommend this book as a handy Data Science reference.

5.0 out of 5 stars Great overview of Data Science

A.C. · 4 November 2019

I'm a PhD student without a background in computer science and i'm looking to go into Data Science. This book gave a pretty great overview of the area and includes info regarding ethics, most of which I had never thought to consider. Would defo recommend to the initial layman.

4.0 out of 5 stars Handy Primer

R.W. · 27 May 2024

I found this a handy primer to the subject and its size made it handy to take as reading material when travelling.

5.0 out of 5 stars Great insight

R.G. · 11 November 2022

Good knowledge base and great for referencing

5.0 out of 5 stars Clear and concise

L.B. · 21 March 2020

Very good summary that allows you to understand the key aspects of the discipline(s) without daunting complexity

3.0 out of 5 stars Interesting read, but offers nothing new

A. · 4 March 2019

I am torn about this book. On one hand, it offers a nice overview of DS, both some technical aspects and the more "bigger picture"/social impact stuff. On the other hand, it rehashes a lot of stuff that shouldn't have to be covered in here. Namely, the machine learning chapter. A lot of effort has been put into this part, but unfortunately I don't think the section should be part of the book (at least it shouldn't be covered as extensively). I get that ML is a huge part of DS, but DS is more than that. This book fails to showcase this, and this mars the overall nice experience of reading this.

5.0 out of 5 stars Very useful intro to data science

T.S. · 21 November 2018

If you want a simple overview of data science and the main issues surrounding the topic then this book is ideal.

5.0 out of 5 stars Excellent intro to data science

C.G. · 14 November 2018

Excellent book of data science, that not only covers algorithms, but also important topics as ethics. Great value for the price

Good introduction to data science

D.H. · 9 November 2019

(function() { P.when('cr-A', 'ready').execute(function(A) { if(typeof A.toggleExpanderAriaLabel === 'function') { A.toggleExpanderAriaLabel('review_text_read_more', 'Read more of this review', 'Read less of this review'); } }); })(); .review-text-read-more-expander:focus-visible { outline: 2px solid #2162a1; outline-offset: 2px; border-radius: 5px; } This is an easy-to-read guide to data science. I think it covers the subject quite widely and is accessible to the general reader.Even though I have studied data science through online courses and other books, I still found things of interest in this book.What I found to be most interesting was the explanation of the CRISP-DM methodology which seems to be absent from the other data science sources I had been exposed to.If you want to explore data science, start with this book before moving onto books by Cathy O'Neill, or courses on Coursera or Edx.

O livro nos apresenta uma ideia geral sobre Data Science

l.p. · 26 July 2021

Os autores se propuseram a apresentar e discutir os fundamentos da ciência de dados.Para tanto, ao longo do texto aprsentam as principais definições da área, além de discutirem a questão da privacidade dos dados e ética na aquisição/uso dos dados.

Claro y sencillo

C. · 23 August 2019

Completo y claro

Explica bien los detalles del tema.

O.M. · 22 June 2020

Buen libro. Directo al tema desde los primeros capítulos. Bien explicados. Intro que te sirve para entender más el tema y entrar a detalle luego de conocer el panorama completo

A map of Data Science

Z. · 29 June 2018

A small book covering essentials of the subject. Absolutely must for amateurs and beginners of Data Science.