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Its very good for quick prototyping. I have used it for experimentation and it speeds up your iterations by a significant amount. From my blog post [1] - "I e

Its very good for quick prototyping. I have used it for experimentation and it speeds up your iterations by a significant amount. From my blog post [1] - "I explored a whole bunch of options on what platform to use for training ML - Scikit Learn, Tensorflow, AWS Machine Learning and Microsoft Azure. Azure’s ease of use puts it in another league altogether - especially for people who want to just apply existing ML algorithms. Drag and drop, kicking off experiments parallely, easy to construct flows etc. allow you to move really really fast as compared to writing code. This might become a bottleneck later as we scale or it might become more expensive to run - but the tools they provide save tons of time, especially for prototyping and experimentation. I highly recommend trying out Azure - their free tier gives a good taste of what’s possible on their platform." [1] http://blog.doctorc.in/post/156115218607/predicting-medical-chronic-conditions-with-machine http://blog.doctorc.in/post/156115218607/predicting-medical-...

Avalaxy 10y ago
Very interesting! Bookmarking your blog post for later. I'm still deciding whether I should focus on Scikit/TF/AzureML, or multiples. Any comparisons between them are welcome. Would be nice to see a cost breakdown for each of them either (as in development time and $$ to run it).
- BIackSwan 10y ago
  Its very contextual. So the answer is "it depends". Azure ML will cost you since they have a non free tier in $$ whereas the other tools can scale without that. BUT for the other tools which are free in $$ you need more powerful hardware available as you start using larger datasets. Also, the ease of use of Azure is a benefit in itself, you don't need to learn any coding library and how to use it - speeds up your iteration loops. So the dev time spent in Azure will be less than others because of how its designed - I am not so sure about using it on a large production level scale though - haven't hit that case yet. I can't get more specific than this because I don't know what your requirements/constraints are and what sort of resources are available to you.
  - a3camero 10y ago
    Although you can sign up for Bizspark (or if you have a startup: Bizspark Plus) and use quite a bit for free.

Avalaxy 10y ago

Very interesting! Bookmarking your blog post for later. I'm still deciding whether I should focus on Scikit/TF/AzureML, or multiples. Any comparisons between them are welcome. Would be nice to see a cost breakdown for each of them either (as in development time and $$ to run it).

BIackSwan 10y ago
Its very contextual. So the answer is "it depends". Azure ML will cost you since they have a non free tier in $$ whereas the other tools can scale without that. BUT for the other tools which are free in $$ you need more powerful hardware available as you start using larger datasets. Also, the ease of use of Azure is a benefit in itself, you don't need to learn any coding library and how to use it - speeds up your iteration loops. So the dev time spent in Azure will be less than others because of how its designed - I am not so sure about using it on a large production level scale though - haven't hit that case yet. I can't get more specific than this because I don't know what your requirements/constraints are and what sort of resources are available to you.
- a3camero 10y ago
  Although you can sign up for Bizspark (or if you have a startup: Bizspark Plus) and use quite a bit for free.