Python for Science and Engineering, Part 2
Dr. Edward Schofield (Python Charmers) bio
100min ◊◊ Intermediate
Sunday 01:10pm, Corinthian
categories:
advocacy, algorithms, biology, case study, engineering, science, statistics, visualisation
This is Part 2 of a showcase in solving a variety of interesting scientific and engineering problems using Python, NumPy, and SciPy, and producing beautiful plots with Matplotlib.
The focus is on the "wow" factor: "Wow! You can do all that in just a few lines of Python?!"
Sample topics discussed include:
- speech and image recognition (how to be head-hunted by Google)
- bioinformatics (how to cure cancer)
- statistical modelling (how to predict the stock market)
The intended audience is graduates in science and engineering disciplines; Python users who want to know more about what's possible with tools like NumPy and SciPy; and users of high-level packages like Matlab or R and low-level languages like Fortran who want to get more interesting work done with less effort.
The focus is on the "wow" factor: "Wow! You can do all that in just a few lines of Python?!"
Sample topics discussed include:
- speech and image recognition (how to be head-hunted by Google)
- bioinformatics (how to cure cancer)
- statistical modelling (how to predict the stock market)
The intended audience is graduates in science and engineering disciplines; Python users who want to know more about what's possible with tools like NumPy and SciPy; and users of high-level packages like Matlab or R and low-level languages like Fortran who want to get more interesting work done with less effort.
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