msalahi

4 ms·

1. 1.▲
   by msalahi 13y ago

   SCIENCE!
2. 2.▲
   by msalahi 13y ago

   "doing all of the web" will cause pretty much any approach to AI/machine learning/NLP to break down. i'm a big believer in it being the responsibility of the engineer employing these techniques to take stock of the
3. 3.▲
   by msalahi 13y ago

   i've actually found the performance of gensim (the topic modeling python module i use here) to be pretty great. we're not at a scale where CPU performance is make or break just yet, so i haven't done any comprehensive testing
4. 4.▲
   by msalahi 13y ago

   In fact, if your training corpus is sufficiently large, you'd be shocked how many words you can eliminate right away for a term frequency of one or two. I went from millions of words in the vocabulary to something like 60k just by igno
5. 5.▲
   by msalahi 13y ago

   As with most successful applications of machine learning, it's about finessing your approach based on the problem at hand. In our case, we have classes divided on the level of "Medicine," "Real Estate," etc. So, we
6. 6.▲
   Teaching a Computer to Read: NLP Hacking in Python(blog.scripted.com)

   104 points by msalahi 13y ago|24 comments