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Spark Machine Learning Samples for IBM Bluemix

Below is a quick overview of samples that demonstrate how to use the machine learning capabilities in Spark on IBM Bluemix.

Flight Delay Predictions

David Taieb posted the slides of his hands-on session how to predict flight delays based on historical data and whether predictions. The sample uses the machine learning algorithms Logistic Regression, Random Forrest, Decision Tree and Naive Bayes.

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Rock-Paper-Scissors Game

When playing rock-paper-scissor everyone has his/her own strategies, e.g. always throw rock. The sample recognizes these patterns and leverages the patterns and history data to predict moves (via the FPGrowth algorithm).

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Titanic Survival Predictions

Manisha Sule describes in her article how to predict whether certain persons would have survived Titanic based on a decision tree algorithm.

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Online Advertising Click Through Rate Predictions

In another sample Manisha explains how to predict click through rates, which is an important metric for evaluating online ad performance, via Logistic Regression.

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Drop off Locations of Taxis

On developerWorks there is a tutorial describing how to determine the top drop off locations for New York City taxis using a popular algorithm known as KMeans.

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Movie Recommendations

Last week I posted an article describing how to run the movie recommendations sample that comes with Spark on Bluemix. To predict ratrings it uses the Collaborative Filtering technique.

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