Regression-based neural networks with TensorFlow v2.0

Regression-based neural networks with TensorFlow v2.0

In this particular example, a neural network is built in Keras to solve a regression problem, i.e. one where our dependent variable (y) is in interval format and we are trying to predict the quantity of y with as much accuracy as possible.

Keras is an API used for running high-level neural networks — the API is now included as the default one under TensorFlow 2.0, which was developed by Google.

The main competitor to Keras at this point in time is PyTorch, developed by Facebook. While PyTorch has a somewhat higher level of community support, it is a particularly verbose language and I personally prefer Keras for greater simplicity and ease of use in building and deploying models.

In this particular example, a neural network is built in Keras to solve a regression problem, i.e. one where our dependent variable (y) is in interval format and we are trying to predict the quantity of y with as much accuracy as possible.

tensorflow machine-learning data-science regression neural-networks

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