C4W4_DeepLearning.AI TensorFlow Developer Specialization

Hello everybody,

on the last assignment of course4/week 4 in [DeepLearning.AI TensorFlow Developer Specialization] we are building a model to forecast the dataset “daily-min-temperatures.csv”.

The dataset hat a total of 3650 datapoints and in the excercise we are predicting and evaluate the points from 2500 to 3650.

I was wondering how I need to adjust the code if I want to predict further datapoints. For example 3651-4000. Of course I can not evaluate then, but I would like to forecast it.

Can anybody help?

Thank you ver much.

It seems like you are asking how to predict multiple points into the future.
Let’s call the number of points you want to predict into the future as F
Please adjust your the following functions in the notebook:

  1. Function windowed_dataset should return the inputs and outputs correctly. In your case, it’ll be a F number of points for prediction.
  2. The final layer of the model architecture should output F time steps instead of 1 time step.