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Getting Started With Python |
If you are interested in the non-statistical areas of predictive analytics such as text mining and machine learning, then you will want to learn Python. Python is the programming language of choice for non-statisticians.
Here are some Python resources:
(1) The official Python homepage is provided at Python Programming Language - Official Website.
(2) The popularity of Python and its large user group help it maintain a large number of web resources. If you are new to Python, then you can learn the basics of Python at Beginner's Guide to Python.
(3) Installations of Mac OSX and Linux will come with versions of Python pre-installed. If you are running a windows machine or if you want to install the most recent version of Python, then visit the Download Page. You will want to be using Python 3, not the older Python 2.
(4) Download and install IPython as an IDE for Python development. IPython
Learning IPython for Interactive Computing and Data Visualization by Rossant If you want to become a serious Python programmer, then you will want to use an IDE or Integrated Development Environment. There are several options for Python IDEs: Spyder, Python(x,y), and IPython. IPython is the newest IDE, and possibly the new standard. |
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Learn Python the Hard Way: A Very Simple Introduction to the Terrifyingly Beautiful World of Computers and Code by Zed Shaw Python will be introduced to students in Predict 400, but I would encourage students to learn the basics of Python before they enter the course. 'Learn Python the Hard Way' is a programmer's introduction to programming. The only way to learn how to program is to write programs. It is no different than many other activities. Nearly all activities require that you develop 'muscle memory' in order to be good. Programming is no different. This book will walk you through several basic programming activities that are typically taught to freshmen and sophomores. Whatever your age, if you are new to programming, then you need to start with the basics. Also see my 'Getting Started with Python' page for useful Python links. |
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Practical Programming: An Introduction to Computer Science Using Python by Gries et. al Once you learn the basics of Python, then you can learn a little more with this book. It might be a good idea to use this book in conjunction with Shaw's 'Learn Python the Hard Way'. |
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NumPy Cookbook by Idris Useful quick start to NumPy for the Python beginner. |
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NumPy Beginner's Guide by Idris Learn about NumPy in a non-cookbook format. |
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Learning SciPy for Numerical and Scientific Computing by Blanco-Silva Learn how to use SciPy for effective Python programming. |
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Python Essential Reference by David M. Beazley If you already know how to program, but are new to Python, then this is probably a good starting point for you in terms of a Python reference book. |
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The Python Standard Library by Example by Doug Hellman This book is an intermediate Python book that will walk you through the Python Standard Library with downloadable code for reference. |
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Matplotlib for Python Developers by Sandro Tosi Want graphics? Then you will have to learn to use Matplotlib. |
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Python for Data Analysis by Wes McKinney |
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Machine Learning by Stephen Marsland Intoduction to machine learning techniques with sample Python code. |
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Machine Learning in Action by Peter Harrington Another introduction to machine learning techniques with sample Python code. |
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A Primer on Scientific Programming with Python by Hans Petter Langtangen A very nice introduction to scientific computing (numerical analysis) using Python. |