Project : Flight Fare PredictionThis project is aimed at predicting flight fares based on several features such as total stops, airline, journey month, departure hour, arrival hour, and duration hours.Major Duties in Flight Fare Prediction Project (End-to-End):1. Data Mining: Extracted relevant data from diverse sources, exploring it for potential insights and trends to be utilized in model development.2. Data Management: Managed large datasets, ensuring efficient storage, retrieval, and organization of data throughout the project lifecycle.3. Data Mapping: Mapped complex data attributes to appropriate model inputs, ensuring proper feature selection and transformation for machine learning algorithms.4. Data Quality and Integrity: Performed checks on data integrity, identifying and rectifying inconsistencies and missing values to ensure reliable and accurate predictions.5.Data Cleaning: Handled noisy and inconsistent data, performing tasks such as handling missing data, outlier detection, and normalization to prepare it for analysis.6. Data Extraction: Retrieved data from databases and files using SQL queries and Python scripts for subsequent analysis.7.Data Preprocessing: Applied techniques like feature scaling, encoding categorical variables, and splitting data into training and testing sets to optimize model performance.8. Machine Learning Model Development: Built a predictive model using the Random Forest Regressor algorithm, tuning hyperparameters and validating performance through cross-validation techniques.9. Data Reporting: Generated clear and actionable reports using data visualization libraries (Matplotlib, Seaborn) and tools (Power BI, Excel) to communicate the results to stakeholders.Skills Highlight:Programming & Analysis: Python, Pandas, NumpyData Visualization: Matplotlib, Seaborn, Power BI, ExcelDatabase Management: SQLMachine Learning: Random Forest Regressor, Data Preprocessing Techniques