Projects
Capstone Project: Hotel Cancellation Prediction
 Hotel booking cancellation is biggest hardships for the Revenue Management.
 The various techniques used in the predictive model building are descriptive statistics, outlier  treatment, need for data standardization, and various performance metrics to validate the performance of predictions on Test & Train sets along with model tuning.
 Creating a Business Report with all the Insights and Recommendations based on the machine learning models predictions for the Revenue Management.
Models: CART, Random Forest, KNN, Gradient Boosting.
Bank Customer Segmentation:
 Using the concepts of Hierarchical and K-Means clustering for the bank customer segmentation and create clusters as Max payers or Full Payers, Non Payers, Revolvers.
 The various techniques used are descriptive statistics, outlier treatment, impact of scaling on clusters, cluster profiling.
Models: Agglomerative Clustering, K-Means Clustering.
Visualizing Insurance Claims using Tableau:
 Explore the art of problem-solving with the aid of visual analytics.
 Creating charts with parameters and calculated fields.
 Build interactive dashboards and storyboard to provide high-level insights.
Intern (Data Science)
Chakra Networks, Research Centre IIT
Madras 05-16 – 06-16
Project: Wholesale Store Sales Prediction Created a new Deep Learning based Hybrid model for Stock Prices prediction.
 Summer Internship Project on Power Line Carrier Communication Management.
 A Smart Meter with user interface to remotely access the power usage measurements stored at the central hub database with features of power management.