Skill

Explore Gradient Descent & Back Propagation

February 2024 with Jonathan Barrios

Join Jonathan Barrios as we learn how to train machine learning models to improve their predictions. We're focusing on how models learn from data, how to measure and improve their accuracy, and how to use special methods for improving during training.

Recommended Experience

Familiarity with basic programming concepts, especially Python
Understanding of math concepts like algebra and calculus
Experience working with datasets, including organizing and dividing them for analysis

Related certifications

None in particular

Related Job Functions

Machine learning engineer
Data scientist
AI researcher

Keith discovered a love for computers and networking in 1984 and began his IT career in 1985. He specializes in networking and security.

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Skill Outline

1. Introduction (6:02)
2. Gradient Descent (5:23)
3. Forward Propagation (6:45)
4. Back Propagation (5:57)
5. Build a Linear Regression Model (9:58)
6. Challenge: PyTorch Research (1:04)

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