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📈 Stock Market Analytics & Price Prediction

Python Streamlit TensorFlow Status

An end-to-end data analytics and predictive modeling project that analyzes 10+ years of stock market data (2014–2024) to uncover trends, visualize insights, and predict future stock prices using Machine Learning and LSTM deep learning models.

📂 Dataset: Historical Stock Market Data (2014–2024) 🧠 Model: Trained LSTM (.h5)

✨ Key Features

📊 Long-Term Market Analysis Analyzes over a decade of stock market data to identify trends, cycles, and volatility patterns.

🧹 Data Cleaning & Preprocessing Handles missing values, scaling, feature selection, and time-series sequence generation.

📈 Exploratory Data Analysis (EDA) Visualizes stock prices, moving averages, daily returns, and volume trends.

📉 Technical Indicators Implements indicators like Simple & Exponential Moving Averages to understand price momentum.

🤖 Machine Learning Models Builds baseline regression models for performance comparison.

🧠 Deep Learning with LSTM Uses Long Short-Term Memory networks to capture long-term dependencies in time-series data.

📐 Model Evaluation Evaluates predictions using RMSE, MAE, and actual vs predicted price plots.

🛠️ Tech Stack

Programming: Python

Data Analysis: Pandas, NumPy

Visualization: Matplotlib, Seaborn

Machine Learning: Scikit-Learn

Deep Learning: TensorFlow / Keras (LSTM)

Tools: Jupyter Notebook, Git, GitHub

📂 Project Structure ├── Stock_Market_Analytics_Project.ipynb # Full analysis, EDA & modeling ├── stock_market_data_2014_2024.csv # Historical dataset ├── lstm_stock_model.h5 # Trained LSTM model ├── README.md # Documentation

🚀 How to Run Locally Prerequisites

Python 3.8+

Jupyter Notebook

Installation & Setup git clone cd pip install pandas numpy matplotlib seaborn scikit-learn tensorflow jupyter notebook Stock_Market_Analytics_Project.ipynb

📊 Results & Insights

✔ Clear visualization of bullish and bearish market phases

✔ LSTM model effectively captures temporal price patterns

✔ Predictions closely follow real market movements (subject to volatility)

⚠️ This project is for educational and analytical purposes only. Not financial advice.

🔮 Future Scope

🔁 Real-time stock data integration (Yahoo Finance / Alpha Vantage)

📊 Interactive dashboards using Streamlit or Power BI

📰 Sentiment analysis using financial news

🧠 Advanced models like GRU & Transformers

🌐 Web deployment using FastAPI

👤 Contact

JAVED AHMED KHAN 🔗 LinkedIn: https://www.linkedin.com/in/javed-ahmed-khan/

⭐ If you like this project, consider giving it a star!

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An end-to-end data analytics and predictive modeling project that analyzes 10+ years of stock market data (2014–2024) to uncover trends, visualize insights, and predict future stock prices using Machine Learning and LSTM deep learning models.

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