Stochastic Gradient Descent Algorithm With Python and NumPy

Stochastic Gradient Descent Algorithm With Python and NumPy

You'll learn what the stochastic gradient descent algorithm is, how it works, and how to implement it with Python and NumPy. Stochastic gradient descent is widely used in machine learning applications. Combined with backpropagation, it’s dominant in neural network training applications.

In this tutorial, you'll learn what the stochastic gradient descent algorithm is, how it works, and how to implement it with Python and NumPy.

Stochastic gradient descent is an optimization algorithm often used in machine learning applications to find the model parameters that correspond to the best fit between predicted and actual outputs. It’s an inexact but powerful technique.

Stochastic gradient descent is widely used in machine learning applications. Combined with backpropagation, it’s dominant in neural network training applications.

In this tutorial, you’ll learn:

  • How gradient descent and stochastic gradient descent algorithms work
  • How to apply gradient descent and stochastic gradient descent to minimize the loss function in machine learning
  • What the learning rate is, why it’s important, and how it impacts results
  • How to write your own function for stochastic gradient descent

python numpy machine-learning data-science

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