Скачать или смотреть 💼 Predictive Modeling for Business Forecasting Project |

💪 During my second task at InternCareer, I completed a Predictive Modeling for Business Forecasting project that involved several key stages. I started with feature selection and engineering, identifying crucial features that influence business outcomes and transforming variables to optimize model performance.

🎯 Next, I focused on model selection and development, applying regression models such as linear regression and decision trees. I trained these models on historical business data to ensure accurate forecasting. A significant achievement was building an ensemble learning model using RandomForestRegressor, which successfully captured complex patterns within the data.

✅ I then moved on to model evaluation and validation, where I assessed performance using metrics like RMSE and MAE. To ensure the model's reliability, I employed cross-validation techniques and validated it on test datasets. From there, I derived predictive insights, identifying key drivers behind the predictions and generating actionable insights for business decisions.

⏳ Finally, I conducted forecasting and scenario analysis by utilizing the trained model to predict future business outcomes. I adjusted input variables to explore their effects on predictions. The project concluded with a detailed report and presentation, highlighting the model's effectiveness, insights, and strategic recommendations for stakeholders. This entire project was executed using Python in Jupyter Notebooks, showcasing its capabilities in data science.