Coffee Break NumPy: A Simple Road to Data Science Mastery That Fits Into Your Busy Life

by Christian Mayer, Lukas Rieger, Zohaib Riaz

Fear of missing out in data science?

Coffee Break NumPy is a new step-by-step system to teach you how to learn Python’s library for data science faster, smarter, and better. You simply solve practical Python NumPy puzzles as you enjoy your morning coffee.

Educational research shows that practical low-stake puzzles and tests help you to learn faster, smarter, and better.

Over 100,000 online Python students have already improved their coding and NumPy skills with the unique Finxter.com puzzle-based learning technique:

"It has some real meat to the problems. Thank you so much for doing this project! I love it!"

—David C.

"Another great little Python book from Christian and his colleagues. As a practitioner in this field, I really appreciate the focus on real-world problems. I can see my coffee breaks will be full for some time to come!"

—Chris C.

As you work through Coffee Break NumPy, your NumPy expertise will grow—one coffee at a time. It’s packed with 46 NumPy puzzles, 10 practical learning tips, 1 compressed cheat sheets, and 1 new way to measure your coding skills.

You will train wildly important NumPy topics such as

NumPy Arrays: creating, basic array arithmetic, one- and multi-dimensional

Data Types: float, integer, mixed, access, conversion

Shape and Reshape: manipulating, accessing, axis argument

Broadcasting: element-wise operations

Indexing and Advanced Indexing: filtering, Boolean indexing, list indexing

Slicing: one-dimensional, multi-dimensional, NumPy-specifics

As a bonus, you will track your individual Python coding skill level throughout the book.

To get most out of this book, you already have basic Python skills. For example, you’ve read my book “Coffee Break Python” or similar introductory Python material.

So how do you spend your Coffee Break? Python!

211 pages, Kindle Edition

Published August 17, 2019

Reviews

[Vlad Bezden · Rating 5 out of 5]

I really enjoyed reading this book and the reason for it is the way how this book is structured. It has an overview of NumPy, but after that it has 46 puzzles starting from easy to the Data Science type of problems using NumPy. Those puzzles up to the point of the specific task/puzzle. After you solve that puzzle it has a result and explanation for that result. Doing this I was able to learn numpy in a more efficient way, try examples, try them in a different way.
My most enjoyable chapter was 'Practical Data Science' where I was able to look and solve real-world data science problems.
This is my second book in this 'Coffeebreak' book. The first one was the 'Coffee Break Python Workbook', both books are excellent books in expanding Python knowledge.

[taro osawa · Rating 4 out of 5]

numpy初心者の自分にちょうど良かった。これだけじゃ全然足りないと思うけど。