These are chat archives for FreeCodeCamp/DataScience

8th
Jan 2019
Eric Leung
@erictleung
Jan 08 01:24
@galuh1300d I haven't done much in JavaScript and machine learning, but this appears to be promising because it builds upon the well-established Tensorflow framework from Google https://js.tensorflow.org/

This may be interesting for people.

I liked the "infographic" describing five "tribes"i n machine learning:

  1. symbolists ~= likes to use rules and decision trees
  2. Bayesians ~= likes to use Naive Bayes or Markov chains
  3. connectionists ~= likes to use neural networks
  4. evolutionaries ~= likes to use genetic programs
  5. analogizers ~= likes to use support vector machines

http://usblogs.pwc.com/emerging-technology/machine-learning-evolution-infographic/?utm_content=buffer8748f&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer

kayfay
@kayfay
Jan 08 03:42
Alice Jiang
@becausealice2
Jan 08 17:40
@galuh1300d I'm currently working on a project that should hopefully become ML in JS
A bunch of non-ML-y steps before I get to that point, but that's the long term goal
@kayfay My R is rubbish so I am of no use, @GoldbergData or @erictleung might be of some help to you, though
@erictleung My gamer tag in most games is Bayes, does that infographic mean I have to start using Naive Bayes and Markov chains exclusively from now on? :joy:
Gautam
@gautam1858
Jan 08 18:56
Python-Awesome tutorial for Machine Learning as part of a Graduate Program in Machine Learning. Pull requests/changes/stars would be very much helpful. https://github.com/gautam1858/python-awesome
mstellaluna
@mstellaluna
Jan 08 20:11
@gautam1858 Hello, please be aware we do not allow self-promotion in any of the FCC rooms, we consider this spamming and is against our Code Of Conduct (https://code-of-conduct.freecodecamp.org) please remove your post.