The following python notebook walks you through building a Support Vector Classifier on scikit learn. You have already built the support vector classifier in the Single Neuron Networks module as a single neuron network, learning with stochastic gradient descent. The support vector classifier from scikit learn is optimized not as stochastic gradient descent, but as a gradient descent on the true dual objective.
In addition to running the code, extract the values of the Lagrangian. Now go through Section 2.2 of the Reading and see if you can interpret the values of the Lagrangian properly, in addition to verifying the points there.
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