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[Supervised ML] Gradient descent / Learning Rate - 6 본문
AI/ML Specialization
[Supervised ML] Gradient descent / Learning Rate - 6
ghwangbo 2023. 7. 28. 13:35반응형
1. Checking Gradient descent for convergence
How to check if Gradient descent is working well?
1.1 Graph
This graph is called Learning curve. As the iteration increases, the minimum cost should decrease. If the graph remains constant after enough iterations, we call that it has converged
1.2 Epsilon / Automatic convergence test
Let epsilon be 0.001
If the cost function decreaes by epsilon in one iteration, declare convergence
2. Learning Rate
When Learning rate is too large or have a bug in our code
We should identify the problem by looking at the minimum cost function for each iteration graph.
If learning rate is too small, it will take a lot of time to find minimum cost.
Values of Learning rate to try:
0.001 0.01 0.1 .....
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