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Development and Evaluation of a Stock Prediction Model Using LSTM Neural NetworksCheck out
- Developed and evaluated machine learning and deep learning models, including Linear Regression, RandomForest, and LSTM Neural Networks, to predict stock prices using historical market data.
- Applied Python, TensorFlow, Keras, Pandas, and Scikit-learn to build, train, and validate predictive models using RMSE and cross-validation techniques.
- Analyzed model performance and compared forecasting accuracy across multiple algorithms to support data-driven decision-making.
- Demonstrated strong capabilities in machine learning, model evaluation, and statistical analysis through end-to-end AI solution development.