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ml_algorithms/linear_regression_gradient_descent.py
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@@ -158,6 +158,20 @@ def interactive_run():
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tex(f"y = {model.theta[0]:.1f} + {model.theta[1]:.1f} x") # print solution
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tex(f"loss = {model.loss_}")
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# -- visualize
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import matplotlib.pyplot as plt
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tex(f"y = {model.theta[0]:.1f} + {model.theta[1]:.1f} x") # print solution
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tex(f"loss = {model.loss_}")
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mark("> How to run")
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mark(
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"""
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```python
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X, y = random_data()
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theta = [0, 0] # initial values
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model = LinearRegressionGradient(theta)
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model.gradientDescent(X, y, theta) # run "i.e. optimize thetas"
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# print solution
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# print(f"y = {model.theta[0]:.1f} + {model.theta[1]:.1f} x")
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# print(f"loss = {model.loss_}")
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```
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"""
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)
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# -- visualize
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import matplotlib.pyplot as plt
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