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Tie each case study to two-ish practical vertical-focused use cases. For example, for the server log chapter, describe application to ad tech conversion metrics and simple security intrusion detection.
These will typically be in the form of end-of-chapter examples (sketch of the solution and how you'd approach it, but not the solution itself; readership hopefully provides).
Reverse geocoding is the business of turning a lat/long into a named place. Besides a neat party trick it turns out that named places have a few benefits over floating point pairs: a) humans don’t tend to think in floating point pairs.. b) while technically the space is infinite and the lat/long space is finite, in practice the names we use to call places converge rapidly to a very small set (in any given region), and for whatever reason (natural or historical) seem to have an affinity for being hierarchical. Both good properties for clustering, compression, and discovery. -- @kellan
Early next week I'll be doing a deep dive into use cases and industries, so
I'll be revisiting this thread with hopefully some helpful ideas at that
time.
On Fri, Jan 25, 2013 at 3:36 AM, Philip (flip) Kromer < [email protected]> wrote:
Geographic data:
refineries at geographic points
transport by truck, boat, rail or pipeline
assume demand is sized by population
Use a greedy algorithm to route fuel to customers
—
Reply to this email directly or view it on GitHubhttps://github.com//issues/5#issuecomment-12693853.
Tie each case study to two-ish practical vertical-focused use cases. For example, for the server log chapter, describe application to ad tech conversion metrics and simple security intrusion detection.
These will typically be in the form of end-of-chapter examples (sketch of the solution and how you'd approach it, but not the solution itself; readership hopefully provides).
/cc @dhruvbansal @joeman @timgasper -- super practical hardnosed use cases invited
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