Summary

In this chapter, we have come quite a long way covering the TensorFlow landscape and its corresponding methods. We got acquainted with how to set up basic regressors, classifiers, and single-hidden layer neural networks. Even though the programming TensorFlow operations are relatively straightforward, for off-the-shelf machine learning tasks, TensorFlow might be a little bit too tedious. This is exactly where SkFlow comes in, a higher-level library with an interface quite similar to Scikit-learn. For incremental or even out-of-core solutions, SkFlow provides a partial fit method, which can easily be set up. Other large scale solutions are either restricted to GPU applications or are at a premature stage. So for now, we have to settle for ...

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