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I don't know exactly whether it is useful for your case, but you can use last day of the week, so coordinates of the object at end of the week. I copied your example data to a text file, read it with Pandas, and resampled data from daily to weekly by getting coordinates of the last day of each week. df = pd.read_csv('untitled.txt', ...


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Better to use Collab indeed. Kaggle also provides notebooks with 38h GPU and also 30 hours of TPU per week you might want to have a look at that as well (plus Kaggle allows you to use your GCP credentials so you can link private google cloud storage buckets to your Kaggle notebook). On Kaggle you will also find plenty of public notebooks that can be of great ...


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You can use RNN architectures like LSTM, and GRU. RNNs take input vectors in each time step, so you can add your extra data to input vector. Your input shape will be batch_size x sequence length x num_of_features.


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Would something like this work? I simply add an extra column that indicates the row number (which is later used as the x-axis) to make sure all values are displayed as a new point instead of plotting on top of each other for the same day. I then specifiy the custom x ticks and labels by selecting the first row for each day and get the row number (which ...


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