Added code for NN

1-first-project/tdt/README.md

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+# Notes on 1st project
+
+The given data at [iui-datalrelease1-sose2021-readonly/\*](/opt/iui-datarelease1-sose2021) represents sensor data from a pen.
+
+| Data   | MinVal | MaxVal | Description                                     |
+| ------ |:------:|:------:| ----------------------------------------------- |
+| Millis |   -    |   -    | Timestamp from tablet (Unix time)               |
+| Acc1 X |   -    |  32768 | Front/Tip accelerometer (Direction: Left/Right) |
+| Acc1 Y |   -    |  32768 | Front/Tip accelerometer (Direction: Up/Down)    |
+| Acc1 Z |   -    |  32768 | Front/Tip accelerometer (Direction: Back/Front) |
+| Acc2 X |   -    |   8192 | Back accelerometer (Direction: Left/Right)      |
+| Acc2 Y |   -    |   8192 | Back accelerometer (Direction: Up/Down)         |
+| Acc2 Z |   -    |   8192 | Back accelerometer (Direction: Back/Front)      |
+| Gyro X |   -    |  32768 | Gyroscope sensor                                |
+| Gyro Y |   -    |  32768 | Gyroscope sensor                                |
+| Gyro Z |   -    |  32768 | Gyroscope sensor                                |
+| Mag X  |   -    |   8192 | Magnetometer                                    |
+| Mag Y  |   -    |   8192 | Magnetometer                                    |
+| Mag Z  |   -    |   8192 | Magnetometer                                    |
+| Force  |   -    |   4096 | Force applied                                   |
+| Time   |   -    |   -    | Time from start of "recording"                  |
+
+There were 100 participants.
+
+The folder-structure is as follows:\
+`/opt/iui-datarelease1-sose2021/{P}/split_letters_csv/{N}{A}.csv`
+
+| Variable | Description                           | 
+| -------- | ------------------------------------- |
+|     P    | The ID of the participant             |
+|     N    | The N-th letter the participant wrote |
+|     A    | The letter that was written           |
+
+Each participants folder contains a `calibration.txt`, which contains the calibration data of the pen for the participant.
+
+Sensor data was recorded at 100hz (100 recordings/s => 1 recording/ms).
+
+## Preprocessing
+
+### General
+
+Since information has different scale (i.e. Acc1: [-32768;32768] and Acc2 [-8192;8192]) the information has to be valued differently based on their importance.
+
+### Millis
+
+- Could be used for identifying each data entry -> needs to be normalized to the first entry of the data set to see the comlete timeline of the data
+
+### Acc1
+
+todo
+
+### Acc2
+
+todo
+
+### Gyro 
+
+todo
+
+### Mag
+
+todo
+
+### Force
+
+- Sometimes sensor data was recorded even when there is no action -> we need to determine the area of interest 
+  - maybe sliding window, where window avg has to be certain threshold
+  - general threshold aproach (filter out data below threshold)
+  - more ideas welcome
+  
+- Data could be normalized by each users relative strength or data entry 
+
+### Time
+
+## Neural Network
+This segment are notes dedicated to the neural network itself.
+
+### Ideas
+
+- Don't use batch normalization but normalize by maxval of sensor
+
+### Results
+
+```python
+model = Sequential()
+
+model.add(Flatten(input_shape=X_filter[0].shape))
+
+model.add(BatchNormalization())
+
+model.add(Dense(1560, activation='relu'))
+
+model.add(Dense(750, activation='relu'))
+
+model.add(Dense(300, activation='relu'))
+
+model.add(Dense(156, activation='relu'))
+
+model.add(Dense(26, activation='softmax'))
+```
+
+```
+Evaluate on test data
+82/82 [==============================] - 0s 3ms/step - loss: 1.4249 - acc: 0.7299
+```
+
+todo: more testing