Data scientist | Machine learning | Data visualization | R | Python | SAS
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Melanoma-Detection-Using-CNN
December 5, 2023 – December 5, 2023
Melanoma-Detection-Using-CNN — GitHub repository
View ProjectTelecom_Churn_Case_Study
October 29, 2023 – October 29, 2023
Telecom_Churn_Case_Study — GitHub repository
View ProjectHouse_Price_Prediction_Advanced_Regression
September 20, 2023 – September 20, 2023
House_Price_Prediction_Advanced_Regression — GitHub repository
View ProjectBoombikes-Linear_Regression-Assignment
August 16, 2023 – August 16, 2023
Linear Regression performed on the Boombikes bike rental dataset as part of an assignment for coursework in the course Executive PG in Machine Learning and AI from IIIT Bangalore.
View ProjectLendingClubCaseStudy
July 5, 2023 – July 5, 2023
In this project, we are working on applying the knowledge of Exploratory Data Analysis to understand how consumer attributes and loan attributes influence the tendency of default for the Lending Club using dataset which includes complete loan data for all loans issued by Lending Club through the time period 2007 to 2011.
View ProjectProject-Boston-Housing
October 16, 2019 – October 16, 2019
Project-Boston-Housing — GitHub repository
View ProjectPROJECT-ON-TELE-MARKETING-CAMPAIGNS-OF-EUROPEAN-BANKING-INSTITUTIONS
April 8, 2018 – April 8, 2018
The data is about telemarketing campaigns of a European banking institution. The European bank wants to predict which clients will secure a term deposit based on a set of information on client and purchase of term deposit. The marketing is usually based on phone calls. Often, a client need to be persuaded multiple times in order to assess if the product (bank term deposit) would be or not subscribed. Predictive modelling approach will help the bank to manage their telemarketing campaign efficiently. So basically, here we will start our project with having a brief outline of the project i.e. by adopting certain methodology to proceed further. Here we will use CTQR consulting framework and DER analytics framework. From which we will decide which modelling technique to be applied and the technology to be used is also decided. After deciding these we will proceed with the project and the first part here is we will check for the missing values and the outliers. And after that imputation of
View ProjectGetting-Started-with-Python-wrt-Datascience
January 19, 2018 – January 31, 2018
Getting-Started-with-Python-wrt-Datascience — GitHub repository
View ProjectProjects-using-R
January 19, 2018 – February 16, 2018
Projects-using-R — GitHub repository
View ProjectCultural Fit Analysis
The candidate's project portfolio indicates a strong interest in data science applications across various domains (finance, housing, telecom, medical imaging). This aligns well with a data scientist role that requires diverse problem-solving. However, the lack of professional experience or team-based projects makes it difficult to fully assess cultural fit in a collaborative work environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.