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I can certainly see a role for somebody that understands the tradeoffs of each of these algorithms and that understands how to properly select and prepare dataa

I can certainly see a role for somebody that understands the tradeoffs of each of these algorithms and that understands how to properly select and prepare dataasets. But I wonder how many people will really need to be able to actually implement these algorithms.

tel 15y ago
They're brutally simple to implement much of the time. The difficulty comes in two places: 1. Derivation of slight variations on the basic principles 2. Scaling. Both are very difficult.
ramblerman 15y ago
That was also the whole point of the stanford ML course. TO teach exactly that skillset. Sure we did some basic implementations in octave, it helps to have some idea of the internals. But that wasn't the goal of the course.
- Drbble 15y ago
  Well, no. ml-class was a series of demos. Plugging in a formula is 1-line developing an algorithm. The original cs229 is more like what you describe.
- Drbble 15y ago
  Well, no. ml-class was a series of demos. The data was all curated in advance and the models pre-selected appropriately.