TensorFlow

Notes

Google Cloud Data Engineering Certification Course

Building TensorFlow Models: GCDEC/Building_Tensorflow/Notes

Deploying TensorFlow Models: GCDEC/Deploying_Tensorflow/Notes

Engineering TensorFlow Models: GCDEC/Engineering_Tensorflow/Notes

Usage and Components

Command Line Arguments

TensorFlow/Command Line Args - notes on using command line arguments in TensorFlow models

Github

Other Repositories

Official Repositories

• https://github.com/tensorflow/tensorflow - official TensorFlow repository

• https://github.com/tensorflow/models - models and examples built with TensorFlow
  • contains models referenced by TensorFlow tutorials in the documentation: https://www.tensorflow.org/tutorials/
  • a partial list of other models: imagenet, adversarial networks, OCR, autoencoders, compression, im2txt, inception, optimizer, GPU, streetview, video prediction

• https://github.com/GoogleCloudPlatform/training-data-analyst - models and examples for the TensorFlow section of the Google Cloud Data Engineering training
  • relevant code is in courses/machine_learning/
  • contains sequential buildup of a simple tensorflow example into a more complex tensorflow example in courses/machine_learning/tensorflow
  • contains example bundled app for training/predictions using Cloud ML Engine in courses/machine_learning/cloudmle

• https://github.com/GoogleCloudPlatform/cloudml-samples - examples that demonstrate how to use Cloud ML Engine; this demonstrates multiple techniques:
  • training a Keras model using Cloud ML Engine
  • using "canned" TensorFlow estimator
  • using custom TensorFlow estimator
  • using low-level TensorFlow API
  • both linear and deep models
  • wide and deep network

Other Repositories

• https://github.com/pdsmith1223/rntn - recurrent neural networks and recursive neural tensor networks

• https://github.com/ajschumacher/mapreduce_with_tensorflow - an unusual use of TensorFlow to perform MapReduce computations