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| | www.analyticsvidhya.com
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| | Interpretable machine learning is key to understanding how machine learning models work. In this article learn about LIME and python implementation of it.
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| | A few posts back I wrote about a common parameter optimization method known as Gradient Ascent. In this post we will see how a similar method can be used to create a model that can classify data. This time, instead of using gradient ascent to maximize a reward function, we will use gradient descent to minimize a cost function. Lets start by importing all the libraries we need:
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| | Learning by doing: predicting the outcome.
| | codeincomplete.com
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| Personal Website for Jake Gordon