Using Kubernetes for Ingesting CSV's to train Deep Learning Models

Running Postgres on kubernetes locally While this may be overkill, its better than configuring a kubernetes cluster on gcloud or whatever else and if done correctly will translate to a cloud service we can later use in a production system while allowing us to focus on micro services individually. To start Kubernetes locally I am using Docker for mac which comes with Kubernetes v1.9.8 as of this time of writing and while it may not perfectly replicate a development/staging/prodcution environment, I find it to be much more straightforward to develop in this manner due to many of the new Kubernetes toolings. »

TensorFlow 0.7.0 dockerfile with Python 3

edit: everything has since been updated to Tensorflow 0.7.0 which I based off of my base cuda dockerfile to use with tensorflow or theano (depending on my goals, Keras allows great flexibility in between training vs compiling) TensorFlow In 2015 Google came out with a new deep learning framework/tensor library similar in many ways to Theano and I enjoy using it a lot more than Theano simply due to long compile times of Theano when using Keras and TensorBoard. »