Developing machine learning solutions that give a lift from your existing prediction algorithms is not an easy task. They require a multitude of activities to get it right including cleaning up the data, setting up the infrastructure, testing &re-testing the model & finally deploying the algorithm.
Here are five machine learning services that can help reduce the pain of deploying your machine learning solution.
Based on Microsoft’s Azure Cloud Platform, Azure Machine Learning offers a streamlined experience for all data scientist skill levels, from setting up with only a web browser, to using drag and drop gestures and simple data flow graphs to set up experiments. Machine Learning Studio features a library of time-saving sample experiments, R and Python packages and best-in-class algorithms from Microsoft businesses like Xbox and Bing. Azure ML also supports R and Python custom code, which can be dropped directly into your workspace. Experiments are easily shared, so others can pick up where you left off.
Google’ Cloud Prediction API provides pattern-matching and machine learning capabilities. Given a set of data examples to train against, you can create applications that can perform the following tasks:
The Algorithms.io cloud platform makes it easy to use machine learning algorithms to classify streaming data from connected devices. Algorithms.
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