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Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
I used `get_splits(train_labels, valid_size=.2, stratify=True, random_state=23, shuffle=True)`. In this case, I would expect the second label to be "Valid" instead of "Test". I'm not specifying any test split and by...
### Issue Description I've noticed a potential issue in the implementation of the _TSSequencerEncoderLayer class, where the LSTM layer appears to be applied along the channel axis (feature size) instead...
In timeseriesAI, all the demos use predefined datasets, such as get_UCR_data(dsid, return_split=False). If you want to use your own prepared data, how can you call it before data reading and...
Why are the parameters non-trainable? And how do we change them to trainable?
Any chance you will add support for time series segmentation in the future? So that each model we create outputs a vector for each timestep instead of for the whole...
https://github.com/timeseriesAI/tsai/blob/main/tutorial_nbs/15_PatchTST_a_new_transformer_for_LTSF.ipynb ... remember that tsai requires that both inputs and outputs have the following shape: [# samples, # features, # steps] I'm wondering can the output shape be: [# samples,...
Hi I want to predict the High price for stock price, using other multivariate features, I'm using the following code snippet to do so import pandas as pd import torch...
The MVTS model can be used for both regression and classification problems. How can I use TST for a regression problem?
First of all, thank you for this inspiring and useful library. I wish to pre-train a TSTabFusionTransformer model and I found the MVP callback (and tutorial). It seems, I would...
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Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai