kvlsky / deep-learning

Punkte

Aufgabe	Punkte
7	14.5/24
8	17.5/22
9

Übung 4 links:

1. http://cs231n.github.io/convolutional-networks/
2. https://wiseodd.github.io/techblog/2016/07/16/convnet-conv-layer/
3. https://towardsdatascience.com/building-convolutional-neural-network-using-numpy-from-scratch-b30aac50e50a

Classifier:

0. install all packages pip -r install requirements.txt
1. download data from https://drive.google.com/drive/folders/1MYGsij12XWBKV5UpOSpzXIoJKv6MRNj0
2. unzip Images.tar using tar -xvzf Images.tar (git bash/mingw/etc.) in classifier root directory

Tasks:

0. RUN ON GPU https://stackoverflow.com/questions/45662253/can-i-run-keras-model-on-gpu
1. save classification model in keras format - h5 [done]
2. create classification report [-]
3. create confusion matrix [done]
4. save plots:
   • accuracy plot [done]
   • report as heatmap [-]
   • confusion matrix [done]

Run on GPU:

1. https://www.tensorflow.org/install/gpu
2. pip install tensorflow-gpu
3. run python
4. sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))