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

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

Author
Christian Mayer, Lukas Rieger, Zohaib Riaz
Publisher
Independently published
Language
English
Year
2019
Page
224
ISBN
1076932614,9781076932617
File Type
pdf
File Size
2.3 MiB

Fear of missing out on 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!

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