Visualization of how learning rate affect gradient descent - how does learning rate affect gd
You can see that gradient descent method is robust - it allows you to optimize a function with a small number of calculations, but it has some drawbacks. The efficiency of the method depends a lot on the choice of the initial parameters, and it is a challenge in machine learning applications to choose the "right" set of parameters to train the model!
In this video I have used visualization for your better understanding that how does learning rate affect gradient descent and how much it is important to have right learning rate.
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