Nearest neighbors and vector models – epilogue – curse of dimensionality

This is another post based on my talk at NYC Machine Learning. The previous two parts covered most of the interesting parts, but there are still some topics left to be discussed. To go back and read the meaty stuff, check out

Nearest neighbors and vector models – part 2 – algorithms and data structures

This is a blog post rewritten from a presentation at NYC Machine Learning on Sep 17. It covers a library called Annoy that I have built that helps you do nearest neighbor queries in high dimensional spaces. In the first part, I went through some examples of why vector models are useful. In the second part I will be explaining the data structures and algorithms that Annoy uses to do approximate nearest neighbor queries.

Nearest neighbor methods and vector models – part 1

This is a blog post rewritten from a presentation at NYC Machine Learning last week. It covers a library called Annoy that I have built that helps you do (approximate) nearest neighbor queries in high dimensional spaces. I will be splitting it into several parts. This first talks about vector models, how to measure similarity, and why nearest neighbor queries are useful.

Presentations about Spotify music recommendations

First one is Neville Li’s presentation about Scala Data Pipelines @ Spotify:

Antipodes

I was playing around with D3 last night and built a silly visualization of antipodes and how our intuitive understanding of the world sometimes doesn’t make sense. Check out the visualization at bl.ocks.org!

Basically the idea is if you fly from Beijing to Buenos Aires then you can have a layover at any point of the Earth’s surface and it won’t make the trip longer.

Software Engineers and Automation

What about software engineers? Every year technology replaces parts of what they do. Eventually surely everything must be replaced? I just ran into another one of these arguments: Software Engineers will be obsolete by 2060.

coin2dice

Benchmark of Approximate Nearest Neighbor libraries

Annoy is a library written by me that supports fast approximate nearest neighbor queries. Say you have a high (1-1000) dimensional space with points in it, and you want to find the nearest neighbors to some point. Annoy gives you a way to do this very quickly. It could be points on a map, but also word vectors in a latent semantic representation or latent item vectors in collaborative filtering.

More Luigi alternatives

3D in D3

I have spent some time lately with D3. It’s a lot of fun to build interactive graphs. See for instance this demo (will provide a longer writeup soon).

D3 doesn’t have support for 3D but you can do projections into 2D pretty easily. It’s just old school computer graphics. I ended up adding an animated background to this blog based on an experiment. The math is simple.