URL(s) with the issue:

In the 1.15 changelog:

https://github.com/tensorflow/tensorflow/releases/tag/v1.15.0

tf.keras.model.save_model and model.save now defaults to saving a TensorFlow SavedModel.

In the 1.15 docstring:
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/keras/Model#save

filepath: String, path to SavedModel or H5 file to save the model. overwrite: Whe

I could not find anything in the docs about how to handle different frequencies of time series. I have a Dataset A with monthly data that i want to use to predict the values from Dataset B that contains quarterly based data. So the target value e.g. quarter 1 is based on the values from month 1-3.

Dataset A (Features):

| Month | Value1 | Value2 | Value3 |
| ------------- | ------------- |

Feedback from some workshop is that we should pay more attention to the quality and working status of the examples we have in the repossitory to help people.

• Have CI running on examples #2353
• Ensure examples works with latest stable version #2351
• Improve documentation by referring to examples
• Once v0.6, stick examples to it

Environment:

Framework: (TensorFlow, Keras)
Framework version:
tensorflow 1.14.0
tensorflow-estimator 1.14.0
tensorflow-serving-api 1.14.0
Keras 2.2.4
Keras-Applications 1.0.8
Keras-Preprocessing 1.1.0
Horovod version:
horovod 0.18.1
MPI version:
(tensorflow_p36) ubuntu@ip-172-31-38-183:~$ mpirun --version
mpirun (Open MPI) 4.0.1
CUDA version:
CUDA Version 10.0.130

NCCL version

Currently we didn't port all test cases from v1alpha1 to v1beta1. Part of the reasons is because we haven't implement functions that v1alpha1 has:

• SyncCache
• [GetSecret](https://github.com/kubeflow/kubeflow/blob/2f15d8dbe85f0081652c1e5

I've ran into this issue for a couple hours and I ended up editing the dist library adding two new functions called fetchVideo and bufferToVideo that works pretty much like the fetchImage and bufferToImage functions.

I'll leave it here to help somebody else with the same issue and in case someone wants to include it on future releases.

face-api.js

...
exports.fetchVideo = fetc

Support for storing large tensor values in external files was introduced in #678, but AFAICT is undocumented.

This is a pretty important feature, functionally, but it's also important for end users who may not realise that they need to move around more than just the *.onnx file.

I would suggest it should be documented in IR.md, and perhaps there are other locations from which it could be s

Revise the documentation in start.md.

Read and try out the examples and tutorials in "Getting Started".
If you find anything unclear or incorrect, please change it in start.md.

External contributors are welcome fo