You can follow along the machine learning tutorial yourself using materials Ezzari Esa has shared at https://github.com/savarin/pyconuk-introtutorial
Syntax tip:
test_data[:,1:]
– comma usage is matrix/2D list slicing
on web development.
You can follow along the machine learning tutorial yourself using materials Ezzari Esa has shared at https://github.com/savarin/pyconuk-introtutorial
Syntax tip:
test_data[:,1:]
– comma usage is matrix/2D list slicing
PyConUK afforded me a great oppportunity to converse with fellow technicians, including those working in HE. Carwyn, based at Bangor University, reminded me about the Software Sustainability Institute, based at the universities of Edinburgh, Manchester, Oxford and Southampton. Whose aim is to support better research by helping researchers to build and use better software.
Damien George, a researcher at the University of Cambridge, has rewritten Python to be optimised for running on a micro controller. For example, the small computers that you might find in your washing machine, sometimes only have 64kb of RAM, so are generally controlled by programs written in C.
MicroPython is implemented on Python 3 and includes the usual Python features, such as:
Uses 528 bytes of RAM at standing and MicroPython will run on various operating systems as well as bare metal.
There are some differences, like not redefining built-ins functions and Micro Python uses garbage collection. For more information https://github.com/micropython/micropython/wiki/Differences
The open source project at: http://github.com/micropython has been well received with over 1200 stars and 170 forks.
More information: http://micropython.org/
As always an entertaining speaker. Harry gave us a world wind tour of the code related to a end of life, open source, project https://github.com/pythonanywhere/dirigible-spreadsheet
He also encouraged any self respecting Pythonista to sign up and register for an account at www.pythonanywhere.com.
Tip: Did you know you could add a name space to eval commands, to limit their scope.
Talk entitled: Collaborative, streaming, 3D, and interactive matplotlib, ggplot2, and MATLAB plots in an IPython Notebook with Plotly by Chris Parmer & Carole Griffiths
The idea behind plot.ly was to bring web standards to graphing and data analysis.
Reason for being: Experiencing teams making graphs in various tools and trying to share it them. This could literally be a case of working with a dedicated graphing tool and then creating and emailing screen shots, as their colleagues all used different tools.
The team wrote a wrapper for iPython to translate graphs into a plot.ly based graphs.
Graphing news feed- https://plot.ly/feed/#sob
Various wrappers exists – https://plot.ly/api/
Various output formats, such as svg, png, available as RESTful calla.
Open source library – cached request model – to handle connectivity breaks.
Can pull graphs back into Python. Also can extract JSON output of the data used in the graph.
No limit on the data storage at this stage. 1/2 million rows have been uploaded say
JavaScript makes this graphing tool available to more people, as the technology is already in their browser.