How to pronounce“bigram”in English

We're going to remove any bigrams that were in common use prior to 1970.

Which is the dummy variable for all bigrams within 10 words of a synonym for risk or uncertainty, which has a position that I'm indexing here with r.

So I'm down waiting bigrams that are kind of ambiguous about in the sense that we could be talking about many different countries and this by the way,

So step one is we're going to identify bigrams, what I'm going to call technical bigram some patents.

And the simplest kind of engram is a bigram, which means two words.

is you want to multiply the weight for each by bigram with what's called the inverse document frequency.

But just think about we're drawing circles around the 305 bigrams and figuring out which are which technology.

And so if you're worried about kind of missing technical bigrams, that's a way of addressing false negatives.

I'm going to go through the all bigrams that are indexed with little b.

Meaning it's in my set of political bigrams but not non-political bigrams.

So then you count all of those mentions of political bigrams in conjunction with the synonym for risk or uncertainty and divide by the length of the transcript.

And then looked around These political but not non political bigrams for synonyms for risk.

The problem with this is that if you want to use even just bigram probabilities,

This is saying, how frequent is the bigram, the Constitution, in the training library for political terms.

So it's actually kind of a tricky question of grouping these 305 bigrams into technologies.

Hi, I have kind of silly question on the bigram.

I'm going to look for them, and I'm going to see if little b bigram is in my set P but not N.

And the top three, what we call the top three bigrams which are associated with disruptive technologies.

Sorry, I should say, you have these 305 bigrams, we're now going to group them into technologies.

a given call, is we're going to count the number of occurrences of political bigrams.

Well, I can reverse that and look for non political bigrams, and see how much risk is associated with these non political bigrams,

And particularly, you can train embedding vectors or embedding vectors basically recognize, it's like you can think of this like an eigenvalue-eigenvectors decomposition of the bigram space.

Some of them, right, because they're n-grams, bigrams, and trigrams-- like, word combinations.

And he said, oh yeah, turns out, from monosyllables, the initial and final bigrams are

In conjunction with a synonym for risk or uncertainty, and then divide by the total number of bigrams in the transcript.