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**Is your feature request related to a problem? Please describe.**
This project aims to predict the stock prices of Netflix using various machine learning techniques. Historical stock data is utilize…
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**Is your feature request related to a problem? Please describe.**
Yes, The art of forecasting stock prices has been a difficult task for many of the researchers and analysts. Investors eagerly seek …
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### Is there an existing issue for this?
- [X] I have searched the existing issues
### Feature Description
Predicting stock prices is an important application of machine learning in finance. we wil…
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1. Data Collection
Gather historical data on:
Indian General Election dates and outcomes.
Historical stock market data (e.g., BSE Sensex and NSE Nifty).
Macroeconomic indicators (e.g., inflati…
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- [ ] ARIMA
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https://github.com/Leci37/TensorFlow-stocks-prediction-Machine-learning-RealTime/blob/386a580efbb2828dd366b20df2a031d45e5f9252/3_Model_creation_models_for_a_stock.py#L6
When running `3_Model_creati…
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Objective: Apply a traditional approach using different models such as Auto Regression, Moving Average, Random walk to do time series analysis on different stock datasets and prediction for the datas…
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Hello there,
what would you recommend as the best torch_dtype param??
Given the tradeoffs??
Or was the model trained only using the bfloat16??
Thanks for the answer.
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Hi, when I run 1.turtle-agent.ipynb file, this error is raised.
```
[Running] python -u "e:\Bourse\Stock-Prediction-Models-master\agent\1.turtle-agent.ipynb"
Traceback (most recent call last):
F…
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I have good knowledge regarding stock market and wanted to combine it with Python to make a prediction model and help other small or big investors to gain some profits.
Please assign me this projec…