Luis Serrano
174 days ago
Machine Learning: Testing and Error Metrics
Machine Learning
A friendly journey into the process of evaluating and improving machine learning models.
- Training, Testing
- Evaluation Metrics: Accuracy, Precision, Recall, F1 Score
- Types of Errors: Overfitting and Underfitting
- Cross Validation and K-fold Cross Validation
- Model Evaluation Graphs
- Grid Search
Confirm Your Email: Send