Summary
Deep learning techniques incorporate many of those improvements
Make predictions on new data
Measure model performance using loss functions
Use loss functions as the basis for gradient descent
Optimize gradient descent to be as efficient as possible
Use performance metrics to make business decisions
Defining ML Models
Mathematical functions with parameters and hyper-parameters
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