November 2012
Beginner
82 pages
1h 48m
English
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Preface
Python, a high-level language with easy-to-read syntax, is highly flexible, which makes it an ideal language to learn and use. For science and R&D, a few extra packages are used to streamline the development process and obtain goals with the fewest steps possible. Among the best of these are SciPy and NumPy. This book gives a brief overview of different tools in these two scientific packages, in order to jump start their use in the reader’s own research projects.
NumPy and SciPy are the bread-and-butter Python extensions for numerical arrays and advanced data analysis. Hence, knowing what tools they contain and how to use them will make any programmer’s life more enjoyable. This book will cover their uses, ranging from simple array creation to machine learning.
Audience
Anyone with basic (and upward) knowledge of Python is the targeted audience for this book. Although the tools in SciPy and NumPy are relatively advanced, using them is simple and should keep even a novice Python programmer happy.
Contents of this Book
This book covers the basics of SciPy and NumPy with some additional material. The first chapter describes what the SciPy and NumPy packages are, and how to access and install them on your computer. Chapter 2 goes over the basics of NumPy, starting with array creation. Chapter 3, which comprises the bulk of the book, covers a small sample of the voluminous SciPy toolbox. This chapter includes discussion and examples on integration, optimization, interpolation, and ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.