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# Kacper SokolSo-Cool

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Created Jan 7, 2019
How to use Markdown as a filter in a Jinja2 template, and then extract the Markdown Meta property directly from the template. Assuming you want to use the Meta-data value before rendering the converted Markdown content (e.g. in the html head), the trick is to render the markdown first, save it to a variable (html_content in this example) using a…
 from pprint import pprint import jinja2 import markdown HTML_TEMPLATE = """{% macro get_html() %} {{ content | markdown }} {% endmacro %} {% set html_content = get_html() %} Title from Markdown meta-data: {{ get_title() }}
Created Jun 30, 2017
HighCharts in Jupyter
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Created Jun 29, 2017
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Last active May 27, 2017
AISB hackathon -- story comprehension

# Automated story comprehension

This notebook shows how to extract background knowledge and relations from a story text. To this end, we use Stanford's NLP parser available to download here.

We parsed the following story (`story.txt` file):

``````Mary was sleeping.
Her phone rang.
She was annoyed.
Ann told the good news to Mary.
``````
Last active Dec 29, 2016
How to find a 'perfect 10'
View find10.md

# How it works?

How to find a 'perfect 10'?

This simple algorithm applies Optional Stopping Time Theorem used for calculating optimal exercising time for American Options. Simply, it tells you whether your current partner is optimal.
Optimality is calculated in a sens of score represented by integer: 1--10, that you assign to your current partner. You also need to specify a few more parameters like:

• score(1--10) of you current partner,
Last active Aug 31, 2016
CuckooML datasets
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Created Apr 5, 2016
Jupyter notebook with sliders
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Created Mar 24, 2016
XKCD in Python
View xkcd.ipynb