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The privacy concerns with throwing loads of data at a third party api is staggering and perhaps the main driver for doing ML in-house.
by myth_buster 12y ago
The privacy concerns with throwing loads of data at a third party api is staggering and perhaps the main driver for doing ML in-house.
- angersock 12y agoIt's not really an important feature--if it was, people wouldn't have been gushing their details into massive databases over the past decade. It's nice to see a set of tools that lets even the most simple of business people exploit their customers as effectively as, say, Facebook or Google.
- agibsonccc 12y agoThis is why I do on premise deployments for my ML stuff. A lot of money is being left on the table with SAAS in this space I think. I'm of the opinion models should come to the data not the other way around.