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Outilne Temporal feature construction

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Presentation on theme: "Outilne Temporal feature construction"— Presentation transcript:

1 Outilne Temporal feature construction
Combining temporal and non temporal features in networks Hyperparameters in networks Hyperparameter optimization Homework: build and submit your first network

2 Hyperparameters Learning rate Optimizers Mini batch size
Constant, exponential, step decay Optimizers Momentum, Adam, Adagrad Mini batch size Early stopping Network architecture Number of hidden units, structure, residual networks Regularization: L2, L1

3 Hyperparameters Activation functions (Relu, Tanh) Random seeds
Model averaging Data preprocessing Element wise standardization, PCA, uniformization, log, square root

4 Hyperparameter optimization
Grid search Random search Further reading:

5 Announcements Next class – 30.4.16
Home work : train a network and submit at least once Automatic tests Instructions Example in Predictor.py Problems tracking – update this file

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