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link to blog post from video 5

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Kevin Markham 2015-05-14 22:26:21 -04:00
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@ -33,7 +33,7 @@ This repo contains IPython notebooks from my scikit-learn video series, as seen
- What are the four steps for model training and prediction in scikit-learn?
- How can I apply this pattern to other machine learning models?
5. Comparing machine learning models in scikit-learn ([video](https://www.youtube.com/watch?v=0pP4EwWJgIU&list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A&index=5), [notebook](http://nbviewer.ipython.org/github/justmarkham/scikit-learn-videos/blob/master/05_model_evaluation.ipynb), blog post)
5. Comparing machine learning models in scikit-learn ([video](https://www.youtube.com/watch?v=0pP4EwWJgIU&list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A&index=5), [notebook](http://nbviewer.ipython.org/github/justmarkham/scikit-learn-videos/blob/master/05_model_evaluation.ipynb), [blog post](http://blog.kaggle.com/2015/05/14/scikit-learn-video-5-choosing-a-machine-learning-model/))
- How do I choose which model to use for my supervised learning task?
- How do I choose the best tuning parameters for that model?
- How do I estimate the likely performance of my model on out-of-sample data?