SGD - futures io
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SGD (Stochastic Gradient Descent) is a popular algorithm for training a wide range of models in machine learning, including (linear) support vector machine, logistic regression. It is an iterative process.

During training one will typically like to see convergence to a best point.

For efficiency it is possible to calculate the gradient after a batch and not for every single training sample.

I Kereas the SGD optimization will take the following parameters :
  • lr : learning rate
  • momentum : momentum
  • decay : decay of the learning rate over each update
  • nesterov : true/false weather to apply Nesterov momentum

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