Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.

from scipy.stats import dirichlet, poisson | |
from numpy.random import choice | |
num_documents = 5 | |
num_topics = 2 | |
topic_dirichlet_parameter = 1 # beta | |
term_dirichlet_parameter = 1 # alpha | |
vocabulary = ["see", "spot", "run"] | |
num_terms = len(vocabulary) |
docker rmi $(docker images -q -f dangling=true) |
<div id="chart"> | |
<h4>Percent of adults over 25 with at least a bachelor's degree:</h4> | |
<p><strong>Median:</strong> <span class="median"></span></p> | |
<small>Source: <cite><a href="http://census.gov">U.S. Census Bureau</a></cite>, via <cite><a href="http://beta.censusreporter.org/compare/01000US/040/table/?release=acs2011_1yr&table=B15003">Census Reporter</a></cite></small> | |
</div> |
# Editor backup files | |
*.bak | |
*~ |