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Stock-Market-Prediction-ML-Project

Stock Market Analysis for Bank of America, CitiGroup, Goldman Sachs, JPMorgan, Morgan Stanley, and Wells Fargo

Phase 1: EDA + Data cleaning:

  • Conducted Exploratory Data Analysis to identify key events including market crashes and stock splits, data fetched from Google Finance
  • Analyzed and classified stocks based on riskiness through financial metrics such as moving averages using Seaborn's and Matplotlib's clustermap to visualize correlations between different stocks.
  • You can also find my comprehensive EDA on TSLA stock fetched from Yahoo Finance to prepare for Phase 2: Modeling using LSTM + Sentiment Analysis

Phase 2: Modeling using LSTM & Sentiment Analysis + Evaluation

  • Employ Long-Short Term Memory (LSTM) RNN and linear regression to predict stock prices, evaluating the predictive power and limitations of each model before integrating them for enhanced accuracy.
  • Conduct sentiment analysis on Elon Musk's tweets to gain insights on their influences on TSLA prices

Phase 3: Dashboard using Streamlit (WIP)

  • Create a dashboard using Streamlit for visualizing stock prices and predictions, integrating sentiment analysis results for comprehensive insights.