Hands-On Challenge Session 3 Predictor.py Building Features
Explore the process of building features using Predictor.py in the hands-on challenge session 3 on 19.03.17. Learn how to initialize data, generate features, and make predictions for testing purposes.
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Dnn: A hands on Challenge session 3: 19.03.17 Predictor.py Building features
Predictor.py Find here http://www.wisdom.weizmann.ac.il/~vision/courses/2017_2/DNN%20Challen ge/files/code/predictor.py Will be used for testing keep signatures Useful functions Don t have to use for training
Predictor.py Initialize: path to raw data 8 data frames no x_y.df Keep signature Resample the glucose every round 15 minutes labels were generated after resampling
Predictor.py Keep signature Input: X Output: predictions (numpy array) 1. Build features 2. Feed to the trained network 3. Return output
Predictor.py Generating features Good to know Example
