How do I learn multivariate time series forecasting?

Course Q&A TensorFlow Developer Professional Sequences, Time Series and Prediction
1

This course teaches univariate time series forecasting

The tensorflow developer certificate requires that we can “Train models to predict values for both univariate and multivariate time series”

I imagine this is an addition to the handbook that did not exist when this coursera course was created

What can I do to learn multivariate time series forecasting in tensorflow?

2

In case anyone is interested, I learnt how to do one form of multivariate time series forecasting by:

  1. attempting to read and understand this notebook: https://www.kaggle.com/code/jaimeggb/multi-variate-time-series-forecasting-tensorflow/edit. I failed, as it was too complex a level for me right now.

  2. reading this: Time Series Forecasting as Supervised Learning. More specifically this part:

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    This was a simple explanation on how to do multivariate forecasting that was directly related to what I learnt for univariate forecasting on TF

  3. then grabbing the dataset from (1) and creating a notebook from scratch using the model and data processing methods I learnt in course 4 to do the Melbourne temperature assignment. This seemed simple at first, with minor changes, but I had to introduce and tweak several things (like scaling, and the model lambda layer for example), but when I managed to get a good forecast it felt like a great accomplishment.

3

Well, I am also having difficulties with Multivariate forecasting using LSTM, and my data is a sensor data that I fetched from an industrial machinery, though, haven’t yet found a solid solution for preparing the data for LSTM, and still on the look! Thank you though for sharing your experience with us!

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