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Projects with source code | Android | Java | LLM | Python | Ai | JSP | Php |

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🌐 Language Detection System – Python Project

Identify the language of any text instantly using Python. A great project for exploring NLP and building multilingual-ready applications.

Key Features
• Detects language from text input with high accuracy
• Supports 50+ global languages
• Uses Python NLP libraries for processing
• Easy-to-understand, modular code suitable for portfolios

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Language Detection System – View Project

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📈 Stock Price Prediction – Python Project

Predict future stock market trends using Python and machine learning. A perfect project for finance, data science, and AI enthusiasts looking to explore predictive analytics.

Key Features
• Real-time stock data fetching and analysis
• Interactive charts for trend visualization
• Predictive model using historical data
• Simple, user-friendly interface for quick insights

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Stock Price Prediction – View Project

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💰 Gold Price Prediction – Python Project

Predict gold price trends using data science and machine learning. Ideal for developers looking to apply forecasting techniques in finance.

Key Features
• Uses historical gold pricing data for modeling
• Employs regression techniques (e.g., Linear Regression, ARIMA)
• Visualizes predicted vs actual price trends
• Built with Python libraries like pandas, scikit-learn, or statsmodels

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Gold Price Prediction – View Project

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📊 Hotel Price Prediction – Python Project

Predict hotel room prices using machine learning and historical data. Ideal for developers exploring regression, time-series models, and pricing strategy tools.

Key Features
• Uses historical hotel data to train prediction models
• Applies regression techniques (e.g., Linear Regression, Random Forest, XGBoost)
• Visual comparison of actual vs. predicted price trends
• Built with Python data libraries like pandas, scikit-learn, or statsmodels

🔗 Explore the full project here:
Hotel Price Prediction – View Project

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🚲 Bike Sharing Demand Prediction – Python Project

Forecast how many bikes will be rented using historical data and predictive analytics. Ideal for those working on urban mobility, time-series forecasting, or ML in smart cities.

Key Features
• Uses historical bike-sharing data with features like weather, hour, day, season, and holidays
• Applies regression models such as Linear Regression, Random Forest, Gradient Boosting, or XGBoost
• Visualizes actual vs. predicted demand trends
• Built with Python data science libraries like pandas, scikit-learn, and possibly Streamlit or Flask for interface

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Bike Sharing Demand Prediction – View Project

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📊 Employee Attrition Prediction – Python/ML Project

Forecast employee turnover using machine learning and HR data. Perfect for developers working on predictive analytics and organizational insights.

Key Features
• Trains models on employee demographics, performance, and engagement metrics
• Predicts attrition risk using algorithms like Logistic Regression or Random Forest
• Provides visual dashboards comparing predicted vs actual turnover trends
• Built with Python libraries such as pandas, scikit-learn, Matplotlib/Seaborn

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Employee Attrition Prediction – View Project

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