Understanding the Training and Validation Loss Curves

Explore the interpretation of various loss curves generated using the Wisconsin breast cancer dataset in this 28-minute video. Learn how to analyze training and validation loss curves to gain valuable insights into the performance of artificial neural networks. Discover the significance of different curve patterns, including underfitting, overfitting, and good fit scenarios. Examine the impact of model parameters, dropouts, and multiple splits on the training process. Download the accompanying code from the provided GitHub repository to practice implementing these concepts and enhance your understanding of neural network training dynamics.

Introduction
Models
Coding
Split
Model Parameters
Results
Dropouts
Multiple splits
Underfitting
Unrepresentative
Good Fit