How can I improve the accuracy of my machine learning model?
There are several strategies you can use, such as feature engineering, hyperparameter tuning, and using more data.
What is feature engineering and how does it help?
Feature engineering involves creating new input features from your existing data to improve model performance.
Can you give me an example of hyperparameter tuning?
Sure! Hyperparameter tuning involves adjusting parameters like learning rate or number of trees in a random forest to optimize performance.
How do I know if my model is overfitting?
You can check for overfitting by comparing the performance of your model on training data versus validation data.
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