Stock price prediction

[Ittismita]

Problem Description:
Developing a new machine learning model for improving the accuracy and performance of stock price predictions. The challenge lies in modeling the highly volatile nature of stock prices using various predictive factors like historical stock prices, market sentiment, trading volumes, and economic indicators.

Model Description:
The primary model will be based on Random Forest Regression, which is well-suited for handling complex datasets with nonlinear relationships. Along with Random Forest, we will also experiment with other models like Support Vector Machines (SVM) and Long Short-Term Memory (LSTM) networks to compare their effectiveness.

Expected time of completion- 3 to 4 days Expected Outcome:
The goal is to enhance prediction accuracy for daily stock price trends, outperforming traditional methods and baseline models. The model will be validated against historical datasets.

As a beginner to contributing in open source, please do assign me this issue under gssoc ext and hacktoberfest 2024, would be a great start for to both open source and a leap in AI/ML. Thank you.

[ananyagoyal1]

Please Assign this task to me under gssoc-extd24 and hacktoberfest

[yashasvini121]

Sure @Ittismita, do mention the estimate time that you will require.

[yashasvini121]

@ananyagoyal1, please check other issues or create a new different one because this has been assigned.

[Ittismita]

Sure @Ittismita, do mention the estimate time that you will require.

Done 👍

[yashasvini121]

Updates @Ittismita?

[Ittismita]

Updates @Ittismita?

So sorry for the delay.. been busy with some university stuff.... would surely submit the PR within the upcoming 2 days...