Last Azure ML Thursdays we explored how to do our Machine Learning in Python. Python in Azure ML doesn't include one particularly succesful algorithm though - xgboost. Python packages are available, but just not yet for Windows - which means also not inside Azure ML Studio. But they are available inside R! Today, we take the same approach
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Last week, we stepped out of Azure ML to look at building ML models in Python using scikit-learn. Today, we focus on getting the trained model back into Azure ML - the place where my ML solutions live in a managed, enterprise environment.
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On this fourth Azure ML Thursday series we move our ML solution out of Azure ML and set our first steps in Python with scikit-learn. Today, we look at using "just" Python for doing ML, next week we bring the trained models to Azure ML. You'll notice there's a lot more to tweak and improve once you do
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Past two weeks, I've explored some applications of Machine Learning by doing a Cortana Intelligence competition (https://gallery.cortanaintelligence.com/competitions). This is a Kaggle-like challenge, but restricted to the Azure ML environment, which creates some challenges of its own. Because the deadline of the challenge is on October 10th, I cannot post all my experiences (yet). So I've
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