This article was published by Przemek Chojecki in November 2019, "[Data Science Books you should read in 2020](https://towardsdatascience. com / data-science-books-you-should-read-in-2020-358f70e1d9b2) ”is a Japanese translation. This article is published with permission from the original author.

Data science is arguably one of the hottest markets right now. Almost all companies are looking for or are considering a data science job.

So it's the perfect time to become a data scientist. Or if you're already a data scientist and want to get promoted to a senior position, it's a great time to hone your skills.

This article covers some of the most popular books on data science.

Introductory level

If you're just starting your data science adventure, give it a try!

Data Science from Scratch As you can see, this is an introduction to data science for complete beginners. You don't need to know Python to get started. ** * Translation: The Japanese translation is [Data Science Starting from Zero-Basics and Practices Learned with Python](https://www.amazon.co.jp/%E3%82%BC%E3%83%AD%E3] % 81% 8B% E3% 82% 89% E3% 81% AF% E3% 81% 98% E3% 82% 81% E3% 82% 8B% E3% 83% 87% E3% 83% BC% E3% 82 % BF% E3% 82% B5% E3% 82% A4% E3% 82% A8% E3% 83% B3% E3% 82% B9-% E2% 80% 95Python% E3% 81% A7% E5% AD% A6% E3% 81% B6% E5% 9F% BA% E6% 9C% AC% E3% 81% A8% E5% AE% 9F% E8% B7% B5-Joel-Grus / dp / 4873117860) **

If you are a complete beginner but want to know more about machine learning, [Introduction to Machine Learning with Python](https://www.amazon.com/gp/product/1449369413/ref=as_li_tl?ie= UTF8 & camp = 1789 & creative = 9325 & creativeASIN = 1449369413 & linkCode = as2 & tag = petacrunch-20 & linkId = 8669cacfe298d25c2832d9062642dd44) is a recommended book. This book also does not assume that you know Python. ** Translation: Japanese translation is [Machine learning starting with Python](https://www.amazon.co.jp/Python%E3%81%A7%E3%81%AF%E3%81%98%E3%82 % 81% E3% 82% 8B% E6% A9% 9F% E6% A2% B0% E5% AD% A6% E7% BF% 92-% E2% 80% 95scikit-learn% E3% 81% A7% E5% AD% A6% E3% 81% B6% E7% 89% B9% E5% BE% B4% E9% 87% 8F% E3% 82% A8% E3% 83% B3% E3% 82% B8% E3% 83% 8B% E3% 82% A2% E3% 83% AA% E3% 83% B3% E3% 82% B0% E3% 81% A8% E6% A9% 9F% E6% A2% B0% E5% AD% A6% E7% BF% 92% E3% 81% AE% E5% 9F% BA% E7% A4% 8E-Andreas-C-Muller / dp / 4873117984) **

Intermediate level

If you've already read one or two data science books, have done one or two projects yourself, and are a little used to working with data, this book will help you grow even further.

Python for Data Analysis It's perfect to become familiar with standard Python libraries like this. It is a book that starts from a place that reminds you of the operation of Python and is completed in one book.

** Translation: Japanese translation is Introduction to Data Analysis with Python **

Python Data Science Handbook A good introduction to all standard Python libraries, including, Matplotlib, and Scikit-learn.

** Translation: Japanese translation is Python Data Science Handbook **

Python Machine Learning Between home levels. Suitable for both professionals and intermediate level and above. It starts slowly and even touches on the latest information on machine learning and deep learning. Please have a look at this!

** Translation: Japanese translation is [Python Machine Learning Programming](https://www.amazon.co.jp/Python-%E6%A9%9F%E6%A2%B0%E5%AD%A6%E7% BF% 92% E3% 83% 97% E3% 83% AD% E3% 82% B0% E3% 83% A9% E3% 83% 9F% E3% 83% B3% E3% 82% B0-% E9% 81 % 94% E4% BA% BA% E3% 83% 87% E3% 83% BC% E3% 82% BF% E3% 82% B5% E3% 82% A4% E3% 82% A8% E3% 83% B3 % E3% 83% 86% E3% 82% A3% E3% 82% B9% E3% 83% 88% E3% 81% AB% E3% 82% 88% E3% 82% 8B% E7% 90% 86% E8 % AB% 96% E3% 81% A8% E5% AE% 9F% E8% B7% B5-impress-gear / dp / 4295003379 / ref = pd_aw_sbs_14_1 / 356-4626260-1375150? _Encoding = UTF8 & pd_rd_i = 4295003379 & pd_rd_r = 95e4d0e9 -4697-b334-fe8e28c202a4 & pd_rd_w = eFfzR & pd_rd_wg = dhEE4 & pf_rd_p = aeee4cf9-9af8-43b4-b05c-0ae7c82d9d5e & pf_rd_r = EV30407MT0TEDRJTE76S & psc = 1 & refR

Python for Finance Must read if you are interested in. It focuses on how to analyze financial markets using data science tools, and there are many great examples of this. This is very practical and suitable for people who do not work in finance on a daily basis.

** Translation: Japanese translation is [Finance with Python](https://www.amazon.co.jp/Python%E3%81%AB%E3%82%88%E3%82%8B%E3%83%] 95% E3% 82% A1% E3% 82% A4% E3% 83% 8A% E3% 83% B3% E3% 82% B9-% E2% 80% 95% E3% 83% 87% E3% 83% BC % E3% 82% BF% E9% A7% 86% E5% 8B% 95% E5% 9E% 8B% E3% 82% A2% E3% 83% 97% E3% 83% AD% E3% 83% BC% E3 % 83% 81% E3% 81% AB% E5% 90% 91% E3% 81% 91% E3% 81% A6-% E3% 82% AA% E3% 83% A9% E3% 82% A4% E3% 83% AA% E3% 83% BC% E3% 83% BB% E3% 82% B8% E3% 83% A3% E3% 83% 91% E3% 83% B3-Yves-Hilpisch / dp / 4873118905 / ref = pd_sbs_14_t_0 / 356-4626260-1375150? _encoding = UTF8 & pd_rd_i = 4873118905 & pd_rd_r = 25e23290-63ee-49ec-8264-5dbbbd1e044e & pd_rd_w = IS3AS & pd_rd_wg = uqGB1 & pf_rd_p = ca22fd73-0f1e-4b39-9917-c84a20b3f3a8 & pf_rd_r = 309AE2AAF53MH3VCP4RF & psc = 1 & refRID = 309AE2AAF53MH3VCP4RF) **

Expert level

When approaching the professional level, it is often more meaningful to actually read a scientific paper than to read a book. However, to go beyond traditional statistics, learning deep learning, this book starts slowly in the solution, provides very practical, ready-to-use code, and in using deep learning. We provide a number of tips that are generally useful. It's also time to implement. Here are three great and currently standard reference books:

Deep Learning with Python Written by the creator of Keras, one of the popular machine learning libraries. A must read for deep learning.

** Translation: Japanese translation is [Deep Learning with Python and Keras](https://www.amazon.co.jp/Python%E3%81%A8Keras%E3%81%AB%E3%82%88%E3 % 82% 8B% E3% 83% 87% E3% 82% A3% E3% 83% BC% E3% 83% 97% E3% 83% A9% E3% 83% BC% E3% 83% 8B% E3% 83 % B3% E3% 82% B0-Francois-Chollet / dp / 4839964262) **

Deep Learning A great reference book. It doesn't contain much code, but it does give you deep insight into how to tackle machine learning problems: written by a pioneer of deep learning.

** Translation: Japanese translation is [Deep Learning](https://www.amazon.co.jp/%E6%B7%B1%E5%B1%A4%E5%AD%A6%E7%BF%92- Ian-Goodfellow / dp / 4048930621 / ref = as_li_ss_tl? ie = UTF8 & qid = 1530541848 & sr = 8-2 & keywords =% E6% B7% B1% E5% B1% A4% E5% AD% A6% E7% BF% 92 & linkCode = sl1 & tag = cfi -22 & linkId = 29c8b4e142d8d7434b5b54080a142a1c) **

If you are interested in math, [Machine Learning: a Probabilistic Perspective](https://www.amazon.com/gp/product/0262018020/ref=as_li_tl?ie=UTF8&camp=1789&creative=9325&creativeASIN=0262018020&linkCode=as2&tag=petacrunch- 20 & linkId = a52c63d00ba9f01f29e1db95d6b4c171) I think you like it very much. This is a masterpiece that covers the mathematics behind all machine learning methods. You probably can't read it all at once, but it's a great reference for machine learning research.

** Translation: Japanese translation unknown **

in conclusion

That's all!

If you find this article interesting, take a look at my other posts on how to become a data scientist.

Complete guide to become a Data Scientist
Practical guide to become a Data Scientist
Data Science Books and Courses recommendations

** Translation: "Data Science Books and Courses recommendations" has been deleted because the link cannot be skipped from the original work **

Translation cooperation

Original Author: Przemek Chojecki Thank you for letting us share your knowledge!

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[PYTHON] Books on data science to read in 2020