Enhancing Real-Time Data, Model Performance, and Scalability #76
Labels
enhancement
New feature or request
good first issue
Good for newcomers
gssoc-ext
GSSoC'24 Extended Version
hacktoberfest
Hacktober Collaboration
hacktoberfest-accepted
Hacktoberfest 2024
level3
45 Points 🥉(GSSoC)
Is this a unique feature?
Is your feature request related to a problem/unavailable functionality? Please describe.
The current reliance on historical data limits the predictive accuracy of the stock price models, making it challenging to respond to real-time market fluctuations. This situation undermines the effectiveness of our predictions and could lead to significant inaccuracies.
Proposed Solution
Real-Time Data Integration: Integrate live data feeds from APIs such as Alpha Vantage or Yahoo Finance to ensure predictions reflect current market conditions, enhancing accuracy and responsiveness.
Advanced Model Optimization: Leverage LSTM models and hyperparameter tuning to improve forecasting performance, along with advanced techniques like cross-validation to mitigate overfitting and ensure robust generalization.
Scalability Enhancements: Revamp the data pipelines to support larger datasets and implement cloud solutions (e.g., AWS Lambda) for dynamic scaling, ensuring the system remains efficient under increased load.
Screenshots
No response
Do you want to work on this issue?
Yes
If "yes" to above, please explain how you would technically implement this (issue will not be assigned if this is skipped)
To implement real-time data integration, I will research relevant APIs for seamless live data ingestion. I will apply LSTM frameworks to improve model architecture and utilize libraries for effective hyperparameter tuning. Additionally, I will redesign the data processing pipeline for scalability and deploy cloud services to enhance performance
Please assign me this issue .
@rohitinu6
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