11–19 of 19 posts
If any YC startups are interested in checking out Azure, note that Microsoft grants $60k in usage credits (as well as architecture and engineering support). Shoot me a mail at felix.rieseberg@microsoft.com and I'll help you out!
I think saw a couple of differentiators from Google's prediction engine. Would someone happen to have a more comprehensive view of how this is different from Google Prediction API?
Other differences are that Azure also has a data transformation component, a built-in text analysis tool, it can perform clustering tasks, and it makes it easier to expose your trained models as APIs.
Of course Azure is a __much__ more complex service, but I am currently working in a somehow similar project: https://www.datapal.io The main goal of this project is to make it easy for people without knowledge in predictive analytics to use their stored data in order to make predictions. __It is still a very early prototype__, therefore the "predictive power" is not great yet, and all kind of bugs are expected. I hav…
Some real world examples here. http://blogs.technet.com/b/machinelearning/archive/2014/07/1... There's also the Azure Machine learning university program with videos etc., but looks like it's for partners only, perhaps will be available to all once it's out of preview. https://readytogo.microsoft.com/global/_layouts/RTG/Campaign...
https://readytogo.microsoft.com/global/_layouts/RTG/Download...
Of course Azure is a __much__ more complex service, but I am currently working in a somehow similar project: https://www.datapal.io The main goal of this project is to make it easy for people without knowledge in predictive analytics to use their stored data in order to make predictions. __It is still a very early prototype__, therefore the "predictive power" is not great yet, and all kind of bugs are expected. I hav…
I think there is a big craze with regard to ML. Most people just draw a black box call it ML/Brain/"hire data scientist" without realizing that for most nontrivial problems its not going to work like magic. Some of the things that I see people underestimating is; a) how hard it is to make the magic black box b) amount of data you need c) how clean the data needs to be d) at times, you need lots of human annotated dat…
My take is that Azure "just" makes it easier/quicker to run ML experiments, and to deploy models. It's not entirely black box since you have to pick an algorithm and parameters. I expect that once you've run your experiments and found what works best, you should be able to get similar results with an open source implementation of your chosen algorithm. But then you'd still have to deploy your model somewhere — maybe using a platform like yhathq.com which makes things more transparent?
Of course Azure is a __much__ more complex service, but I am currently working in a somehow similar project: https://www.datapal.io The main goal of this project is to make it easy for people without knowledge in predictive analytics to use their stored data in order to make predictions. __It is still a very early prototype__, therefore the "predictive power" is not great yet, and all kind of bugs are expected. I hav…
I've thought about doing this myself, but it's a lot of work. I applaud your effort. I have a lot of experience with internet marketing, perhaps I can help out.
I think there is a big craze with regard to ML. Most people just draw a black box call it ML/Brain/"hire data scientist" without realizing that for most nontrivial problems its not going to work like magic. Some of the things that I see people underestimating is; a) how hard it is to make the magic black box b) amount of data you need c) how clean the data needs to be d) at times, you need lots of human annotated dat…
Of course Azure is a __much__ more complex service, but I am currently working in a somehow similar project: https://www.datapal.io The main goal of this project is to make it easy for people without knowledge in predictive analytics to use their stored data in order to make predictions. __It is still a very early prototype__, therefore the "predictive power" is not great yet, and all kind of bugs are expected. I hav…
Sounds very exciting! This space is getting a bit crowded though (see http://www.quora.com/Who-are-the-main-competitors-to-the-Goo... ). How would you differentiate Datapal from competitors such as BigML, Predictobot, etc.?