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  # Stock_Analytics
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  Stock Prediction and Analysis Script Overview This script is designed to predict stock prices using various machine learning and statistical models. It fetches historical stock data, processes it, and then applies several predictive models. The results, including forecasts and model coefficients, are saved to an Excel file for further analysis.
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  User Interface: The entire analysis and visualization can be wrapped in a web-based UI using Streamlit. Users can input stock tickers and get visualized results, including price predictions, technical indicators, and risk levels.
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  Custom Styling: The Streamlit app is styled according to user preferences, including setting backgrounds, coloring text and numeric values based on risk levels, and displaying buy signals.
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  Tabs and Layout: Multiple tabs or sections can be created in Streamlit for different types of visualizations like technical indicators, feature importance, and future predictions.
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- 5. LLM Integration
 
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+ ---
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+ title: AI Stock Predictor
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+ sdk: streamlit
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+ emoji: πŸ†
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+ colorFrom: green
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+ colorTo: blue
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+ pinned: true
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+ thumbnail: >-
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+ https://cdn-uploads.huggingface.co/production/uploads/65ad293914e6582c30c688cc/qQkQV_-VsWMgfevm1H9RV.jpeg
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+ short_description: Advanced AI predictions for the next week's stock prices
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+ ---
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+
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+ # πŸ“ˆ AI Stock Predictor
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+
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+ This app provides:
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+ βœ… Advanced AI predictions for the next week's stock prices
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+ βœ… Buy/Sell recommendations with confidence levels
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+ βœ… Stop Loss, Target Price, and Volatility Analysis
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+ βœ… Key Support/Resistance Levels
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+
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+ ### How to Use
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+ 1. Enter a **Stock Ticker** (e.g., `TATAMOTORS.NS`).
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+ 2. Click **Submit** to get insights and predictions.
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+
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+
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  # Stock_Analytics
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  Stock Prediction and Analysis Script Overview This script is designed to predict stock prices using various machine learning and statistical models. It fetches historical stock data, processes it, and then applies several predictive models. The results, including forecasts and model coefficients, are saved to an Excel file for further analysis.
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  User Interface: The entire analysis and visualization can be wrapped in a web-based UI using Streamlit. Users can input stock tickers and get visualized results, including price predictions, technical indicators, and risk levels.
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  Custom Styling: The Streamlit app is styled according to user preferences, including setting backgrounds, coloring text and numeric values based on risk levels, and displaying buy signals.
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  Tabs and Layout: Multiple tabs or sections can be created in Streamlit for different types of visualizations like technical indicators, feature importance, and future predictions.
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+ 5. LLM Integration