Google has launched a service, “Google Prediction API” for developers, that would help them pave a simple way to create a software that learns to handle incoming data. Just like the Google hosted algorithms could be trained for sorting out emails into categories for “praises” and “complaints” using a dataset that offers many examples of both types, similarly, in using API, the future emails can be screened by software and handled accordingly.
Only few hundreds of developers have access to the service and they are already creating amazing things. The users come from different backgrounds and many want to opt for product recommendation.
As a matter of fact, machine learning is not an easy feature to build into a software. There are different mathematical techniques and algorithms that work best for different kinds of data. You need specialized knowledge when it comes to machine learning to consider utilizing it in a product.
Google’s service offers a machine learning black box, wherein the data goes in one end and on the other end, predictions come out. You can see three basic commands, one is to upload a data collection, second to tell the service to learn from it and last to submit new data for the system to react based on what it learned.
Only few hundreds of developers have access to the service and they are already creating amazing things. The users come from different backgrounds and many want to opt for product recommendation.
As a matter of fact, machine learning is not an easy feature to build into a software. There are different mathematical techniques and algorithms that work best for different kinds of data. You need specialized knowledge when it comes to machine learning to consider utilizing it in a product.
Google’s service offers a machine learning black box, wherein the data goes in one end and on the other end, predictions come out. You can see three basic commands, one is to upload a data collection, second to tell the service to learn from it and last to submit new data for the system to react based on what it learned.
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