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

🔵 Intellipaat Data Science with Python course: https://intellipaat.com/python-for-data-science-training/In this Data Science With Python Training video, you...

Applied Data Analysis in Python Machine learning and Data science, we will investigate the use of scikit-learn for machine learning to discover things about whatever data may come across your desk.

Practice your skills in Data Science with Python, by learning and then trying all these hands-on, interactive projects, that I have posted for you.