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Is TensorFlow limited to neural networks only?

Is TensorFlow designed to only implement neural networks? Can it be used as a general machine learning library - to implement all kinds of supervised as well as unsupervised methods (naive Bayesian, decision trees, k-means, SVM, to name a few)? Regardless of the TensorFlow literature that I come across, they usually talk about neural networks. TensorFlow's graphics-based architecture likely makes it a viable candidate for neural networks. But can it also be used as a general machine learning system?

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Tensorflow includes additional machine learning algorithms such as:

K-means clustering
Random Forests
Support Vector Machines
Gaussian Mixture Model clustering
Linear/logistic regression


The above list is taken from here , so you can read this link for more details.

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