Using exploratory data analysis (EDA) achieved department wise performances Top 3 Important Factors a ecting employee performance. Extreme Gradient Boosting Claasi er(XGBoost) giving 93.8% accuracy which can predict the employee performance based on factors as inputs. A trained model used to hire employees Recommendations to improve the employee performance based on insights from analysis.

Create predictive model for inventory forecasting so that service achieve JIT standards. Feature engineering using exploratory data analysis (EDA). Used ARIMA model to predict spare parts.

The problem statement was to calculate customer credit score. Feature engineering and outlier detection using exploratory data analysis (EDA). Using random forests algorithm 96.13% accuracy achieved.

Manager in Data Analyst

Working on Computer Vision Techniques

Creating ChatBot and adding the utterances