@royshouvik I'm on Calculus 1B: Integration, last chapter, and I'm excited for the next part!
I was just wondering, I haven't seen much integration in use in data science personally, differentiation, that's a key, but integration? Hardly seen it anywhere.
How does it apply to data science problems? (I understand that it's very good to know calculus inside out, and it really helped me with my math skills anyways, just asking out of curiosity!)
@cuent: You can definitely use word2vec and cosine distance to find relationships between words, just be aware, relationship does not always mean being synonym, or antonym, or anything like that, the human perspective of "relationship" is not necessarily reflected in word2vec, for example,
good are likely to be very similar to each other in word2vec, it's in the sense that they are both used in similar contexts.
I guess you could train a model to find the relationship you have in mind between words.
As a side note: If you are looking for finding similarities between words in terms of characters, you might find Levenshtein distance useful.