Difference between revisions of "Tutorial: Playing with the Boston Housing Data"

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(Building a Linear Regression Model with SKLearn on the Boston Data)
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The tutorial is best viewed as a Jupyter notebook (available in zipped form below), or as a static pdf (you'll have to retype all the commands...)<br />
 
The tutorial is best viewed as a Jupyter notebook (available in zipped form below), or as a static pdf (you'll have to retype all the commands...)<br />
 
<br />
 
<br />
* [[Media:SKLearnLinearRegressionBostonData.pdf | pdf]]
+
* [[Media:SKLearnLinearRegression_BostonData.pdf | pdf]]
 
* [[Media:SKLearnLinearRegressionBostonData.ipynb.zip | Jupyter Notebook]] (Unzip before using)
 
* [[Media:SKLearnLinearRegressionBostonData.ipynb.zip | Jupyter Notebook]] (Unzip before using)
  

Revision as of 16:25, 8 August 2016

--D. Thiebaut (talk) 16:06, 8 August 2016 (EDT)


Deep Neural-Network Regressor (DNNRegressor from Tensorflow)


This tutorial uses SKFlow and follows very closely two other good tutorials and merges elements from both:


We use the Boston housing prices data for this tutorial.
The tutorial is best viewed as a Jupyter notebook (available in zipped form below), or as a static pdf (you'll have to retype all the commands...)



Building a Linear Regression Model with SKLearn on the Boston Data


This tutorial also uses SKFlow and follows very closely two other good tutorials and merges elements from both:


We also use the Boston housing prices data for this tutorial.
The tutorial is best viewed as a Jupyter notebook (available in zipped form below), or as a static pdf (you'll have to retype all the commands...)