Abstract: We see patterns in the numbers, these patters are following a context, therefore a syntax but this in fact can be very frustrating for things like the nature of the rain, a problem we treat with RNN LSTM Neural Network for Timeseries forecasting, this model is intended to be a starting point for a research on LSTM Deep Learning for Forecasting on Stock Market Analysis.
Insights:
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Model: ADAcore v1.1b (Already trained.)
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Forecasting functions 1-day to 7-day.
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Share differentiation between forecasts.
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Revenue calculator base on forecast.
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Trend Signal (Buy/Sell)
pip install -i https://test.pypi.org/simple/ adaforecasts==1.3.3
import ada.analysis.forecasts as ada
x = ada.forecast('AAPL')
print(x)
Output:
Current Price: 145.4 Forecast (1 Period): 143.14865