7:00 – 5:30 ASRC NASA/PhD

• • Practical Deep Learning for Coders, v3
  • Continuing Clockwork Muse (reviews on Amazon are… amazingly thorough) , which is a slog but an interesting slog. Martindale is talking about how the pattern of increasing arousal potential and primordial/stylistic content is self-similar across scales of the individual work to populations and careers.
  • Had a bunch of thoughts about primordial content and the ending of the current dungeon.
  • Last day of working on NOAA. I think there is a better way to add/subtract months here in stackoverflow
  • Finish review of CHI paper. Mention Myanmar and that most fake news sharing is done by a tiny fraction of the users, so finding the heuristics of those users is a critical question. Done!
  • Setting up Fake news on Twitter during the 2016 U.S. presidential election as the next paper in the queue. The references look extensive (69!) and good.
  • TFW you don’t want any fancy modulo in your math confusing you:

    def add_month(year: int, month: int, offset: int) -> [int, int]:
        # print ("original date = {}/{}, offset = {}".format(month, year, offset))
        new_month = month + offset
        new_year = year
    
        while new_month < 1:         new_month += 12         new_year -= 1     while new_month > 12:
            new_month -= 12
            new_year += 1
    
        return new_month, new_year

  • Got a version of the prediction system running on QA. Next week I start something new