Title: Add Nifty 50 price prediction using LSTM In Machine learning and Data science Intermediate

[deepanshubaghel]

Initiative (Required)

GSSoC 2024 Extd 🚀

Is your feature request related to a problem? Please describe.

The feature request addresses the challenge of accurately predicting Nifty 50 prices by improving the model's ability to capture long-term dependencies and trends in stock market data, which traditional models may struggle to do effectively.

Describe the solution you'd like.

The solution involves implementing an LSTM model to better capture time dependencies and trends in Nifty 50 price data, improving prediction accuracy. This includes optimizing hyperparameters, incorporating additional features like volume or market sentiment, and fine-tuning the model for faster convergence and reliable results.

Add any other context or screenshots about the feature request here.

Please add labels(gssoc-ext , hactoberfest-accepted , Level(1, 2, 3))

[github-actions[bot]]

@deepanshubaghel

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[SakiraAli1115]

I am the mentor of this project. Hello @deepanshubaghel I appreciate your pull issue, can you describe little bit and give screenshots!!

[deepanshubaghel]

I am the mentor of this project. Hello @deepanshubaghel I appreciate your pull issue, can you describe little bit and give screenshots!!

Key features include:

• Data preprocessing with MinMaxScaler and handling missing values using forward fill.
• LSTM model with two layers and Dropout for regularization.
• Evaluation using metrics such as RMSE, MAE, MSE, and R² scores for both training and testing data.
• Visualization of actual vs predicted values and loss metrics across epochs.
• This implementation aims to enhance stock price prediction by leveraging LSTM's ability to model sequential data effectively.

[deepanshubaghel]

@SakiraAli1115 please review it and assign

Please add labels(gssoc-ext , hactoberfest-accepted , Level(1, 2, 3))

[SakiraAli1115]

@Kushal997-das kindly assign this issue

[deepanshubaghel]

@Kushal997-das @SakiraAli1115