Tensorflow continous training from input data
Djboblo,
I assume that you need to predict whole next day values on per minute basis.
In that case your options are:

recursive prediction, i.e. using predicted data as input for the next prediction
structuring the model to provide you with prediction for the whole next day

If it is just a matter of predicting for a single minute forward and your model is trained on reasonably large amount of data - don't worry, just feed it with the values up to the prediction minute. Periodically you may re-train the model using new data.
I‘m new to tensorflow have a general question:
I have a certain amount of training data and want to do a time series prediction.
The intervals on my training data is one minute and I want to do a prediction for the following minutes based on the new input data which is provided via a REST API
What I don‘t understand is this:
Let‘s say I train the model with all the data till yesterday and this means I can predict the first values of today by a certain amount. But the new values of today have not been observed by the model that has been build yesterday.
How would you solve this problem?
Thanks