brilliant intro by emlyn & ruby then keynote, automated fact checking https://pydata.org/london2017/schedule/presentation/66/ https://fullfact.org/about/our-team/
static type analysis https://speakerdeck.com/marcobonzanini/static-type-analysis-for-robust-data-products-at-pydata-london-2017
pip install mypy http://mypy-lang.org/
random forests https://pydata.org/london2017/schedule/presentation/25/ https://github.com/NathanEpstein/pydata-london https://codewords.recurse.com/issues/seven/a-tour-of-random-forests https://spark.apache.org/docs/2.1.0/mllib-ensembles.html
machine learning for artists gene kogan, http://ml4a.github.io/ https://pydata.org/london2017/schedule/presentation/67/ http://genekogan.com/ https://github.com/phillipi/pix2pix https://github.com/ibab/tensorflow-wavenet
data and diversity in the music industry https://pydata.org/london2017/schedule/presentation/39/ meh
https://pydata.org/london2017/schedule/presentation/10/ andryichenko, jupyter https://github.com/rs2/pydata-2017-jupyter-workshop
https://pydata.org/london2017/schedule/presentation/5/ zeigerman, tensorflow conv nets https://github.com/DJCordhose/speed-limit-signs/blob/master/README.md https://notebooks.azure.com/anon-oojjea/libraries/pydata
https://pydata.org/london2017/schedule/presentation/2/ radcliffe, tdda http://www.tdda.info/pdf/tdda-tutorial-pydata-london-2017.pdf
# references
python -m tdda.referencetest.examples
python test_using_referencetestcase.py
# constraints
python -m tdda.constraints.examples
python elements_discover_92.py
tdda verify testdata/elements118.csv elements118.tdda
# then some blah about an automatic regex generator called rexpyhttps://pydata.org/london2017/schedule/presentation/14/ analysis with react blah
source live coded in bit.ly/dutc-tutorial (dropbox)
to check