- PGP in Data Science, Praxis Business School (2018-19) - BE Industrial Engg from College of Engineering Guindy, Anna University, Chennai (2012-16)
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Gesture-recognition-using-CV
March 23, 2019 – March 23, 2019
Gesture recognition and control using Computer vision. This was developed as a capstone project in praxis business school.
View ProjectPython-Interactive-package-for-exploratory-data-analysis
February 28, 2019 – February 28, 2019
Problem Statement: To develop a package in Python which will do the EDA of any dataset.
View ProjectMarketing-Analytics-Hands-on-case-studies
February 15, 2019 – February 15, 2019
Hands on Assignment practice of case studies for the given data set as part of my Marketing Analytics subject in my PGPDS course.
View ProjectMarketing-Analytics---Market-Basket-Analysis
February 12, 2019 – February 12, 2019
Hands on Assignment practice of Market Basket Analysis (Association Rule) for the given data set, as part the Marketing Analytics subject of my course
View ProjectTime-Series-Modelling-for-an-FMCG-sales-dataset
February 4, 2019 – February 4, 2019
Time Series Modelling for an FMCG sales dataset - Our Handson Assignment as part of the PGPDS course
View ProjectPySpark_practice_assignment
January 20, 2019 – January 20, 2019
This assignment is on the application of PySpark during my course.
View ProjectComparing-Linear-Ridge-and-Lasso-for-data-with-multicollinearity
January 18, 2019 – January 18, 2019
A Comparative study on Linear, Ridge and Lasso Regression models for data containing multi-collinear variables
View ProjectLinear-Model-Complexity-and-its-Errors
December 3, 2018 – December 4, 2018
In Linear regression, how model complexity affects the error and also how to chose optimal train dataset size are explained in graphical manner.
View ProjectCultural Fit Analysis
The candidate shows initiative through numerous personal projects, indicating a self-starter attitude. The diversity of projects (computer vision, EDA, marketing analytics, time series) suggests a broad interest within data science. However, without professional experience or team-based projects, assessing cultural fit beyond individual drive is challenging.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are brief, limiting insight into collaboration or problem-solving approaches.