Non Sequitur: An exploration of Python's random module
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| Title | Non Sequitur: An exploration of Python's random module |
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| Part Number | 109 |
| Number of Parts | 119 |
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| License | CC Attribution 3.0 Unported: You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor. |
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| Production Place | Berlin |
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| Abstract | Jair Trejo - Non Sequitur: An exploration of Python's random module
An exploration of Python's random module for the curious programmer, this talk will give a little background in statistics and pseudorandom number generation, explain the properties of python's choice of pseudorandom generator and explore through visualizations the different distributions provided by the module.
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# Audience
Non mathematical people who wants a better understanding of Python's random module.
# Objectives
The audience will understand pseudorandom number generators, the properties of Python's Mersenne Twister and the differences and possible use cases between the distributions provided by the `random` module.
# The talk
I will start by talking about what randomness means and then about how we try to achieve it in computing through pseudorandom number generators (5 min.)
I will give a brief overview of pseudorandom number generation techniques, show how their quality can be assessed and finally talk about Python's Mersenne Twister and why it is a fairly good choice. (10 min.)
Finally I will talk about how from randomness we can build generators with interesting probability distributions. I'll compare through visualizations thos provided in Python's `random` module and show examples of when they can be useful in real-life. (10 min.) |
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