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Tuesday, June 18, 2019

More on MIT Open Source AutoML: ATMSeer

More on the topic, and some additional background information and links.  Very powerful concept that that should continue to expand.  Automation is the word,   See also Google AutoML, at tag below.

MIT Researchers Open-Source AutoML Visualization Tool ATMSeer    by  Anthony Alford   ... 

A research team from MIT, Hong Kong University, and Zhejiang University has open-sourced ATMSeer, a tool for visualizing and controlling automated machine-learning processes.
Solving a problem with machine learning (ML) requires more than just a dataset and training. For any given ML tasks, there are a variety of algorithms that could be used, and for each algorithm there can be many hyperparameters that can be tweaked. Because different values of hyperparameters will produce models with different accuracies, ML practitioners usually try out several sets of hyperparameter values on a given dataset to try to find hyperparameters that produce the best model. 

This can be time-consuming, as a separate training job and model evaluation process must be conducted for each set. Of course, they can be run in parallel, but the jobs must be setup and triggered, and the results recorded. Furthermore, choosing the particular values for hyperparameters can involve a bit of guesswork, especially for ones that can take on any numeric value: if 2.5 and 2.6 produce good results, maybe 2.55 would be even better? What about 2.56 or 2.54?

Enter automated machine learning, or AutoML. These are techniques and tools for automating the selection and evaluation of hyperparameters (as well as other common ML tasks such as data cleanup and feature engineering). Both Google Cloud Platform and Microsoft Azure provide commercial AutoML solutions, and there are several open-source packages such as auto-sklearn and Auto-Keras.  ...."

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