Machine Learning / Initialize Model

Azure Machine Learning Studio provides many different state-of-the art machine learning algorithms to help you build analytical models.

First, identify the general type of machine learning task you are performing, as the algorithms grouped in each category are tailored to specific predictive tasks.

If you need help selecting an algorithm, see these resources:

• Machine learning algorithm cheat sheet for Microsoft Azure Machine Learning Studio

• How to choose Azure Machine Learning algorithms for clustering, classification, or regression

After you have chosen an algorithm and configured its parameters, you can then use one of the training modules to run data through the chosen algorithms, or you can use Tune Model Hyperparameters to iterate over all possible parameters and determine the optimal configuration for your task and data.

Having built and trained a model, typically your next step is to use one of the Machine Learning / Score modules to generate predictions based on the model.

You can use the modules in the Machine Learning / Evaluate section to measure the accuracy of the model, based on the scores you’ve generated.