Sharon Goldwater: Vectors and their uses

A nice, self-contained introduction to vectors and why they are a useful mathematical concept. You should consider this reading ESSENTIAL if you haven't studied vectors before (or it's been a while).

A nice, self-contained introduction to vectors and why they are a useful mathematical concept. Available online

I’d also highly recommend watching the video series the Essence of Linear Algebra on the 3blue1brown youtube channel. If you’ve not got much experience with these concepts, watch chapters 1-4 in this series, and chapter 9 on the dot product.

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- October 28, 2016 at 10:23 #5667
  Simon
  Professor
  Discuss here
- October 31, 2016 at 09:55 #5725
  Haitong Z
  Student
  We use cosine similarity to estimate the distance in case of high-dimensionaity. So, in speech recognition, what are the other possible dimensions, except for F1 and F2?
- November 1, 2016 at 12:07 #5773
  Simon
  Professor
  You could imagine doing speech recognition by measuring the cosine similarity between feature vectors. But this is not the usual way.
  
  We typically use a generative model (the Gaussian, or Normal, probability density function) of feature vectors, within a generative model of sequences (a Hidden Markov Model).
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Sharon Goldwater: Vectors and their uses

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