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kaieye/2022-machine-learning-specialization
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I'm working through the kaieye/2022-machine-learning-specialization notebooks. I'm stuck on the gradient descent exercise in Course 1. Walk me through what each step does and why it works.
Using the logistic regression notebook from kaieye/2022-machine-learning-specialization, explain what the cost function is doing in plain English without requiring math background.
Help me understand the reinforcement learning section from Course 3 of the 2022 ML Specialization. What does Q-learning do and how does the notebook example demonstrate it?
I want to run kaieye/2022-machine-learning-specialization notebooks locally. Walk me through installing Python 3.7.6 and getting the first exercise notebook running.
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