Machine Learning Guide
A machine learning podcast teaching the fundamentals of machine learning and artificial intelligence. It covers intuition, models, neural networks, math, languages, frameworks, etc. Where visual ML resources provide the trees, I provide the forest. Podcasts are a great supplement during exercise, commute, chores, etc.
MLG 015 Performance
May 07, 2017
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Performance evaluation & improvement
Try a walking desk to stay healthy while you study or work!
Show Notes
Performance evaluation
- Performance measures: accuracy, precision, recall, F1/F2 score
- Cross validation: split your data into train, validation, test sets
- Training set is for training your algorithm
- Validation set is to test your algorithm's performance. It can be used to inform changing your model (ie, hyperparameters)
- Test set is used for your final score. It can't be used to inform changing your model.
Performance improvement
- Modify hyperpamaraters
- Data: collect more, fill in missing cells, normalize fields
- Regularize: reduce overfitting (high variance) and underfitting (high bias)