Understanding Machine Learning for Stock Price Prediction

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Explore the world of machine learning in stock price prediction, covering algorithms, neural networks, LSTM techniques, decision trees, ensemble learning, gradient boosting, and insightful results. Discover how machine learning minimizes cost functions and supports various learning paradigms for classification and regression tasks.

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  1. MACHINE LEARNING IN STOCK PRICE PREDICTION CARL CEDERBORG FACULTY MENTOR: DR. CARLOS ARIAS HONORS PROGRAM DIRECTOR: DR. CHRISTINE CHANEY

  2. WHAT IS MACHINE LEARNING? Algorithm that learns from data Minimize a Cost Function Supervised/Unsupervised/Semi-supervised/Reinforcement Learning Classification/Regression

  3. NEURAL NETS AND GRADIENT DESCENT

  4. LSTMS

  5. DECISION TREES

  6. ENSEMBLE LEARNING AND GRADIENT BOOSTING

  7. RESULTS

  8. WHAT MORE? Serve one master

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