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Test tensorflow:
python -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))"
===Sample CNN Projects===
There are some nice Tensorflow CNN tutorials online:
*https://www.tensorflow.org/tutorials/estimators/cnn
*https://www.tensorflow.org/alpha/tutorials/images/intro_to_cnns
*https://www.tensorflow.org/tutorials/images/deep_cnn
Some of which use standard datasets:
*https://medium.com/tensorflow/introducing-tensorflow-datasets-c7f01f7e19f3
The code for MNIST.py is in E:\projects\tensorflow.
===Word2Vec===
There's a nice Word2Vec guide with code and data here: https://www.tensorflow.org/tutorials/representation/word2vec
==DIGITS==
DIGITS runs in docker containers. See https://docs.nvidia.com/deeplearning/digits/digits-release-notes/running-digits.html
As root run:
docker run --runtime=nvidia --name digits -d -p 5000:5000 nvidia/digits
Then browse to http://192.168.2.202:5000
===Notes===
Docker won't run if you left a container with the same name running (active or not). List docker containers:
docker ps -a
Stop a container:
docker stop containername
Prune them (-a is all, -f is no prompt)!
docker system prune -af
If you do a full prune, then docker will download a new image for nvidia/digits:latest
