Posted by When you start a Machine Learning project, one of the hardest parts is figuring out which algorithm to use and how to tune it to perform well. That process can take days or weeks and usually requires significant technical experience. Well, OptiML makes that work simple! It automates model selection and parameter optimization for classification and regression, so you can focus on the problem, not the setup.
With a simple 1-Click in the BigML Dashboard, OptiML can launch a full search across decision trees, ensembles, logistic regression, and deepnets. You can also set your own limits, choose the metric you want to optimize, and define how long the system should explore. Behind the scenes, techniques like Bayesian optimization and Monte Carlo cross-validation keep the search efficient and reliable. OptiML builds and evaluates hundreds of models, handles issues like missing data and class imbalance, and returns a ranked list of the best performers. You can run it through the Dashboard, the API, or WhizzML, and you still get full visibility into the process.
To see how this works step by step, we invite you to watch the video below.
If you prefer a podcast to learn about OptiML, please click here. And for more learning resources to keep on exploring OptiML, please visit this dedicated page.
More BigML resources explained in minutes will come soon, stay tuned!
The Official Blog of BigML.com 