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updated stock price prediction tutorial
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‎machine-learning/stock-prediction/data/AAPL_2020-04-28.csv

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‎machine-learning/stock-prediction/data/TSLA_2020-09-03.csv

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‎machine-learning/stock-prediction/parameters.py

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BATCH_SIZE = 64
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EPOCHS = 400
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# Apple stock market
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ticker = "AAPL"
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# Tesla stock market
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ticker = "TSLA"
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ticker_data_filename = os.path.join("data", f"{ticker}_{date_now}.csv")
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# model name to save, making it as unique as possible based on parameters
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model_name = f"{date_now}_{ticker}-{LOSS}-{OPTIMIZER}-{CELL.__name__}-seq-{N_STEPS}-step-{LOOKUP_STEP}-layers-{N_LAYERS}-units-{UNITS}"

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