MISSION 237

Gradient Descent

Learn how to fit a model using gradient descent.

Objectives

  • Learn about optimization problems.
  • Learn the theory behind the gradient descent algorithm.

Mission Outline

1. Introduction
2. Single Variable Gradient Descent
3. Derivative Of The Cost Function
4. Understanding Multi Parameter Gradient Descent
5. Gradient Of The Cost Function
6. Gradient Descent For Higher Dimensions
7. Next Steps
8. Takeaways

Course Info:

Linear Regression for Machine Learning

Intermediate

The average completion time for this course is 10-hours.

This course requires a premium subscription and includes five missions and one guided project.  It is the 21st course in the Data Scientist in Python path.

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