Evaluation Metrics, Overfitting and Underfitting in Machine Learning Models - Episode 3.5

Evaluation Metrics, Overfitting and Underfitting in Machine Learning Models - Episode 3.5

Donato Capitella via YouTube Direct link

- Introduction

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- Introduction

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Classroom Contents

Evaluation Metrics, Overfitting and Underfitting in Machine Learning Models - Episode 3.5

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  1. 1 - Introduction
  2. 2 - Evaluating Models
  3. 3 - Accuracy, Precision and Recall
  4. 4 - Confusion Matrix
  5. 5 - Overfitting and Underfitting
  6. 6 - Regularization L1/L2, Dropout
  7. 7 - Data Augmentation and Improving Models
  8. 8 - Bonus Lab: Evaluting the MNIST Model
  9. 9 - Bonus Lab: Building the Confusion Matrix

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