# Machine Learning System Design

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### Recommendation System, pros & cons for different methods

### Advertisement Sorting

### Model performance optimization

bias vs variance

cost / loss function

* naive Bayes
* Linear / Logistic Regression
* Random Forest / Decision Tree

optimization function

### Feature Collections and Selections

### Metrics

* For classification
* For regression
* accuracy
* confusion matrix
* recall
* precision
* F score
* ROC, AUC
* Multi-class classification

### Unbalanced Data

### Bias - Variance

* &#x20;Andrew's class

### Miss labeled Semi supervised learning



