I want to do cloud machine learning using google's CloudML offering.
Google cloud might interoperate well with a bunch of google products, such as tensorflow. I use that. Let's see how it works.
Obviously this will work better if you commit to googly storage APIs etc.
Note (2017-02-14): Google supports python 2.7 only - so be prepared to party like it's 2010. (Is this still so?)
Seems to also support VMs?
There is the usual thicket of weird service names.
Basic workflow bits are
- cloud storage stores data
- dataflow supplies data
- model fitting done using cloudml
- control this from datalab
Also good to know:
- HOWTO for Tensorflow
- also has a minimal docker-free version for the command-line-happy
- HOWTO for Apache Spark
Painstaking run through
See How is Google number crunching awful?.
Google now has their own instruction manual for one common use case, tensorflow. Tensorflow without a phd.
Just saw a gentleman called @ankutkotwal claiming that Google cloudml does some neat AutoML. MMMV. Recommend hyptertuner for parameter selection?