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

Using xplain To Interpret Model Results

Joachim Zuckarelli walks us through the xplain package in R: The above XML produces the following output (don’t worry too much about the call of xplain(), we will discuss later on in more detail how to work with the xplain() function): library(car) library(xplain) xplain(call="lm(education ~ young + income + urban, data=Anscombe)", xml="") ## ## Call: ## lm(formula = education […]

Read More

Sentiment Analysis Of Hotel California

Sara Locatelli analyzes the lyrics to Hotel California using tidytext: Sentiment analysis is a method of natural language processing that involves classifying words in a document based on whether a word is positive or negative, or whether it is related to a set of basic human emotions; the exact results differ based on the sentiment […]

Read More

Leave a Reply

Your email address will not be published. Required fields are marked *


May 2018
« Apr