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Hey everyone! Glad to be back! Decision Tree classifiers are intuitive, interpretable, and one of my favorite supervised learning algorithms. In this episode, I’ll walk you through writing a Decision Tree classifier from scratch, in pure Python. I’ll introduce concepts including Decision Tree Learning, Gini Impurity, and Information Gain. Then, we’ll code it all up. Understanding how to accomplish this was helpful to me when I studied Machine Learning for the first time, and I hope it will prove useful to you as well.
You can find the code from this video here:
Books!
Hands-On Machine Learning with Scikit-Learn and TensorFlow
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Check out more Machine Learning Recipes here:
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You can find the code from this video here:
Books!
Hands-On Machine Learning with Scikit-Learn and TensorFlow
Follow Josh on Twitter:
Check out more Machine Learning Recipes here:
Subscribe to the Google Developers:
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