Building A Neural Network With TensorFlow

Julien Heiduk gives us an example of building a neural network with TensorFlow:

To use Tensorflow we need to transform our data (features) in a special format. As a reminder, we have just the continuous features. So the first function used is: tf.contrib.layers.real_valued_column. The others cells allowed to us to create a train set and test set with our training dataset. The sampling is not the most relevant but it is not the goal of this article. So be careful! The sample 67-33 is not the rule!

It’s probably an indicator that I’m a casual, but I prefer to use Keras as an abstraction layer rather than working directly with TensorFlow.

Related Posts

Bayesian Neural Networks

Yoel Zeldes thinks about neural networks from a different perspective: The term logP(w), which represents our prior, acts as a regularization term. Choosing a Gaussian distribution with mean 0 as the prior, you’ll get the mathematical equivalence of L2 regularization. Now that we start thinking about neural networks as probabilistic creatures, we can let the fun […]

Read More

Principal Component Analysis With Faces

Mic at The Beginner Programmer shows us how to creepy PCA diagrams with human faces: PCA looks for a new the reference system to describe your data. This new reference system is designed in such a way to maximize the variance of the data across the new axis. The first principal component accounts for as […]

Read More


May 2018
« Apr Jun »