Can tensorflow be used for non-deep learning machine learning?

Can tensorflow be used for non-deep learning machine learning? Like logistic regression, xgboost, random forest etc.?

I just started listening to lesson #8 v1 on my commutes :slight_smile: Hope I will survive the TF :slight_smile: I listened about this today.

This seems to have been a nice initiative. Not sure where it went though? Maybe it got sucked into TF in a fashion similar to Keras?
https://curiosity.com/videos/ml-toolkit-tensorflow-dev-summit-2017-google-developers/

Yes, In a way. Tensorflow is for neural networks (I dont really use Tensorflow so Its possible it supports other algorithms). A single layer neural network is basically the same as logistic regression. @jeremy explains in lesson 6 or 7 of the ML course.

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I see there are few “non-deep learning” algorithms being implemented under tf.contrib : https://github.com/tensorflow/tensorflow/tree/r1.10/tensorflow/contrib