Merry Christmas, dear readers!

Since it’s the season of giving, Packt Publishing offered to organize a contest with prize – 2 print copies and 2 ebooks of my book NumPy Beginner’s Guide.

**The Prize**

What you will learn from NumPy 1.5 Beginner’s Guide

- Installing NumPy
- Learn to load arrays from files and write arrays to files
- Work with universal functions
- Create NumPy matrices
- Use basic modules that NumPy offers
- Write unit tests for NumPy code
- Plot mathematical NumPy results with Matplotlib
- Integrate with Scipy, a high level Python scientific computing framework built on top of NumPy

The book is written in beginner’s guide style with each aspect of NumPy demonstrated by real world examples. You can also download a sample chapter.

**How to Win NumPy Beginner’s Guide**

You can enter by writing a comment to this post explaining **why you would like to have the book**. The contest has already started and will end on **January 31st 2012 at 11:59 PM GMT**. Winners will be randomly chosen and notified by email, after termination of the contest.

The contest is open to everybody in the world, **however print copies are only available to residents of the US and Europe**.

Comments are moderated by me, so your comment will not appear immediately.

**Good luck, readers!**

python enthusiast who is looking to improve everyday .

Since the winner is chosen at random, everyone should have an equal chance in winning one of the prices. I personally will use it in my thesis where I try to map EM-fields to mathematical dipoles in huge matrices with Python an NumPy/SciPy.

I’ll use it in my university project on evolucionary algorithms and more AI tricks I have in mind to implement in Python next year! Thanks!

I am a Senior at FSU, studying scientific computing and I think this book would be a great resource for me!

This book would really help me with my master thesis (mixed classical and genetic algorithm coil optimization methods) and also with other minor university projects (data compression and numerical methods assignments.)

I’d love to find out more on NumPy code testing and plotting.

I’m a security professional who just got into python recently. I will use this book to learn more about numpy to make my everyday job easier.

I am new to Python/NumPy. I am implementing a compressed sensing algorithm to reconstruct images from very sparse data. Having a NumPy manual/reference would be very useful!

I probably deserve it less than others, but I still would love to get my hands on it’s, because, I appreciate the beauty of Python and made it my primary go-to language. NumPy knowledge will make my arsenal richer, and give me more reason to extol Python and further develop knowledge and skills with it.

Blender enthusiast who would like to do numpy things with mesh data.

I have been recently teaching myself Python for the purpose of my upcoming graduate studies. Learning NumPy is next up on my list!

I’d like to give it to my brother who’s in grad school doing genetic mapping and statistical research.

Learning new machine learning and artificial intelligence techniques – would love to start implementing them with Numpy~!!

I want to help convert the other students in my lab from Matlab to NumPy.

I need it because it’s free.

Because I work with a lot of people who could benefit from learning more about numpy, and I deal with it on a day-to-day and would love to have a reference available.

I want to express my strong protest to this unfair contest:

If I wanted to participate it would be because my great interest on numpy. If you ask me if I’m *really* interested I will tell you that yes, I *really* am. If you do not believe me I can support my position revealing to you that I already bought the book last week. However this makes the gift unnecesary… This is unfair. I ask for a reparation !

Hi Joaquin,

The fact that you bought the book last week doesn’t mean that you can’t enter the contest. I am sure you can find somebody else who is also interested in NumPy.

Regards,

Ivan Idris

Oh, I know. I was not complaining !. Contrarily, please consider my post as my (humorous) way to enter the contest. Ah! btw, thanks for the book, (I mean the one I already have) ðŸ™‚

I already learned some new things. great !

Cognitive neuroscience student desperately trying to move away from MATLAB. Research was fun before MATLAB…

I am applying to neuroscience graduate programs, and I want to improve my programming capabilities. They will be a valuable tool, especially if I get into a lab involved in computational neuroscience.

i learnt numpy without Ã book.

reading a good one could make me rediscover numpy

In februari I will start a new job doing astrophysical calculations. They use NumPy (and much more), something I don’t have experience with yet.

I think this book would be a great help.

I want to do a phD in Econometrics. In my field, a lot of people use Matlab and in Europe, Python is practically unknown (by economists/econometricians). Since I try to only use free software only, I want to use Python for my research. This book would be very useful for me.

Looks like a interesting book

It’s not perl! ðŸ™‚

I am not a beginner with numpy; I use it almost everyday with scipy and matplotlib at work for my research. I would find this book quite useful to loan out to people I regularly help to get started on using Python as an alternative to MATLAB, etc.

I just started work on an app that will be analyzing molecular compounds as candidate ligands for binding to precious metals in nuclear waste. The heavy lifting will be handled by some external programs, but I’m going to be doing some analysis and filtering on the results and NumPy/SciPy are high on my to-do list to learn. A nice intro book would be great.

python devleper here, always trying to expand my skillset

and by devleper, i mean developer

I am a Mathematics and Physics major who is highly interested in numerical computing. I’ve tried out NumPy at this years Google AI contest and it was fantastic. Naturally I would like to learn more about it.

I work with python regularly and enjoy pushing the language to its limits. I view NumPy as a separate but highly integral part of the language itself, and I would like to become more accustomed to using it with the same tenacity that I enjoy using the rest of the language.

Expanding one’s pythonic horizons ought universally to be held as a venerable endeavor.

I’d love to learn numpy as it would add to my arsenal of script to do visualization for my server farm ðŸ™‚

I use numpy/scipy on a fairly regular basis as part of my research on vector-space based semantic models at the University of Oxford. These are great tools, combining the easy of use of python and the number-crunching power of C and Fortran-based extensions. I recommend them to anyone getting into any form of scientific computing.

NumPy is black belt level python kung fu!

Because I already read chapter 3, learnt a few tricks and now I want more.

Python+Numpy is the La-Z-Boy of scientific programming.

I’m a cancer researcher and because of my rapid development cycle I would like to move away from my current language (C++) into something easier to develop like python (which I have a basic grip with). I’ve read some online articles and because of the scale of my work (very large bioinformatics datasets) I understand It would greatly speed up development to use NumPy instead of the standard python libraries for some operations.

I just started to learn Python, and this package is mentioned everywhere along the Python ecosystem. This book would be a perfect boost to catch on with it!

I’ve recently been reminded that learning things from books is fun – the structure introduced by an author is helpgul to me.

I’d like to use to improve my understanding of quantum mechanics with simulations.

NumPy offers a natural approach in writing linear algebra code in Python. Created as a free alternative to the expensive Matlab package, it allows for rapid prototyping of a specific class of applications. It is integrated in some specialized packages like Theano (quoting from Theano’s homepage: “tight integration with numpy â€“ Use numpy.ndarray in Theano-compiled functions”) or SciPy. From http://numpy.scipy.org/ it is claimed that it also integrates with legacy code written in C++ or Fortran (yep, old, but a very efficient compiler…) There are plenty of tutorials showing how to use numpy for signal processing and in other challenging areas.

Compared to other numerical targeting packages/languages (like R or Octave/Scilab), the Python + Numpy mix seems to worth investigation: one can use her OOP skills offered by Python in conjunction with a linear algebra package. Developing neural networks or prototyping algorithms in computer vision are supported by Numpy. As Python seems to be the language of choice for developing or prototyping Machine Learning systems (see for eaxmple the answers from http://www.quora.com/What-are-the-best-open-source-machine-learning-libraries-written-in-Python), Numpy is certainly a “must” for anyone interested in developing such softwares.

I am learning Python to make my work more efficient. And from what I have gathered, NumPy makes working with numbers more efficient. So it is all a win-win situation.

I am a technical writer by choice. I win the book. I read it. And if it impresses me, I shall write about it. And I get to learn NumPy. Winnings everywhere! ðŸ™‚

Hoping numpy will be able to help me at my job by processing, predicting and graphing system/application resources usage for service level management.

I’m interested in trying out NumPy instead of R. I see that the book introduces correlations and histograms. Those would be good starting points. The Markov chain tutorial looked interesting as well.