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beginner_source/basics/optimization_tutorial.py
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Optimizing Model Parameters
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===========================
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-Now that we have a model and data it's time to train, validate and test our model by optimizing it's parameters on
+Now that we have a model and data it's time to train, validate and test our model by optimizing its parameters on
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our data. Training a model is an iterative process; in each iteration (called an *epoch*) the model makes a guess about the output, calculates
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the error in its guess (*loss*), collects the derivatives of the error with respect to its parameters (as we saw in
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the `previous section <autograd_tutorial.html>`_), and **optimizes** these parameters using gradient descent. For a more
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