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-N100-stock-model

Third PyTorch project, getting used to the syntax and wordings

How does it work?

You'll have to have the information for the opening, closing, high, low, and adjusted closing prices for the past 7 days. There is an example at the end where the model is trained where I use the test dataset to see how accurate the results are. You can input your information like that. This is ONLY for the ^N100 stock

How did you create it?

I used the kaggle dataset with Global Markets Data across 2008-2023. Here's the dataset: https://www.kaggle.com/datasets/pavankrishnanarne/global-stock-market-2008-present I used an LSTM cell with 16 layers and 64 neurons, as well as batch normalization between the Linear layers so that gradients were more effective since that was a problem I noticed during training. Dropout layers are included to reduce overfitting. I used a sliding window technique to encapsulate my data, using a window of 7 instances.

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2nd stock model that predicts prices for ^N100 stock

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