May I suggest that we bucketize the 1.0 scope into various themes: - Enhanced first experience / user experience - Improving the existing framework - Extending the existing framework (enabling new scenarios/use cases, etc.)
That said, has anyone been thinking about the following? - Natively support Windows (guidance, etc. No documentation exists today, for instance) - Faster time to first application (from discovery to first application currently takes a non-trivial amount of effort; how can we lower the bar and reduce the friction for adoption?) - Better documenting use cases with working samples/examples (Documentation on https://mahout.apache.org/users/basics/algorithms.html is spread out and there is too much focus on algorithms as opposed to use cases - this is an adoption blocker) - Uniformity of the API set across all algorithms (are we providing the same experience across all APIs?) - Measuring/publishing scalability metrics of various algorithms (why would we want users to adopt Mahout vs. other frameworks for ML at scale?) Thanks. On Sat, Mar 1, 2014 at 8:55 PM, Dmitriy Lyubimov <dlie...@gmail.com> wrote: > On Sat, Mar 1, 2014 at 5:05 AM, Sebastian Schelter <s...@apache.org> wrote: > > > > > > > I must say that I think that the architecture of Oryx is really what I > > would envision for Mahout. Provide a computation layer for training > models > > and a serving layer with a REST API or Solr for deploying them. > > > I am dubious about desgination of Mahout as a service (of any kind). It > should be easy to embed and customize, either online or offline. But > service... I am more along the lines of scikit-learn here. The use case > patterns (at least in my case) are hard to fit into a rigid black box. > Looking back (say homonym filtering) i couldn't have done it with a block > box. I'd leave it to infrastructure engineers to put it into ad-hoc > service. > -- Thanks.
