How to train your own model in AWS Sagemaker?
You can convert your Keras model to a tf.estimator and train using the TensorFlow framework estimators in Sagemaker.
This conversion is pretty basic though, I reimplemented my models in TensorFlow using the tf.keras API which makes the model nearly identical and train with the Sagemaker TF estimator in script mode.
My initial approach using pure Keras models was based on bring-your-own-algo containers similar to the answer by Matthew Arthur.
I just started with AWS and I want to train my own model with own dataset. I have my model as keras model with tensorflow backend in Python. I read some documentations, they say I need a Docker image to load my model. So, how do I convert keras model into Docker image. I searched through internet but found nothing that explained the process clearly. How to make docker image of keras model, how to load it to sagemaker. And also how to load my data from a h5 file into S3 bucket for training? Can anyone please help me in getting clear explanation?