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RagaVedhni (RID : 1ate6l7sxu1a6)

designation   Data Scientist

location   Location : Jaipur , India,

experience   Experience : 3 Year

rate   Rate: $24 / Hourly

Availability   Availability : Immediate

Work From   Work From : Offsite

designation   Category : Information Technology & Services

Shortlisted : 4
Total Views : 178
Key Skills
Data science Agglomerative Clustring K-Means Clustring Java Python

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
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.

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