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Lære Challenge: Time Series Forecasting with LSTM | Time Series Analysis
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Challenge: Time Series Forecasting with LSTM

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  • Define the TimeSeriesPredictor class, completing its __init__ method to set up the nn.LSTM and nn.Linear layers, and implement its forward method to process input sequences and output a prediction.

  • Instantiate the TimeSeriesPredictor model, then define the nn.MSELoss criterion and torch.optim.Adam optimizer.

  • Implement the training and evaluation loops, including forward and backward passes, parameter updates, and loss calculation.

Løsning

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Sektion 3. Kapitel 5
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book
Challenge: Time Series Forecasting with LSTM

Opgave

Swipe to start coding

  • Define the TimeSeriesPredictor class, completing its __init__ method to set up the nn.LSTM and nn.Linear layers, and implement its forward method to process input sequences and output a prediction.

  • Instantiate the TimeSeriesPredictor model, then define the nn.MSELoss criterion and torch.optim.Adam optimizer.

  • Implement the training and evaluation loops, including forward and backward passes, parameter updates, and loss calculation.

Løsning

Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

close

Awesome!

Completion rate improved to 4.76

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