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I think it all depends on the purpose of the library and who is a target user. The NNI is a package for tuning neural networks models, it will be mostly used in
by pplonski86 8y ago
I think it all depends on the purpose of the library and who is a target user. The NNI is a package for tuning neural networks models, it will be mostly used in use cases that require deep neural networks, like image classification or voice recognition.
BTW, I think all autoML solutions forget about end users. They all require too much engineering knowledge from the user. I think it will be nice to have an autoML solution that can be used by citizen data scientist.
- minimaxir 8y ago> BTW, I think all autoML solutions forget about end users. They all require too much engineering knowledge from the user. I think it will be nice to have an autoML solution that can be used by citizen data scientist. This is the approach of a project I am currently working on. (and am now explicitly making clear in the README!)
- pplonski86 8y agoCould you provide some link to the project?
- human_scientist 8y agoWhat about approaches like auto-sklearn [1]? With these it is basicaly: >>> automl = autosklearn.classification.AutoSklearnClassifier() >>> automl.fit(X_train, y_train) >>> y_hat = automl.predict(X_test) [1] https://automl.github.io/auto-sklearn/stable/ https://automl.github.io/auto-sklearn/stable/