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Assessing your cultural and operational fit
Vehicle-Insurance-Prediction
June 25, 2025 – July 9, 2025
This project aims to predict whether a customer will purchase vehicle insurance based on demographic and vehicle-related attributes using supervised machine learning techniques. The dataset contains information such as age, gender, vehicle damage history, insurance history, annual premium, and customer response to a past insurance offer.
View ProjectContinuous-Integration-Practice
June 25, 2025 – June 25, 2025
Continuous-Integration-Practice — GitHub repository
View ProjectTravel-Planner-Agent
June 15, 2025 – June 15, 2025
Travel-Planner-Agent — GitHub repository
View ProjectHTSAgent-Task-Pritush
June 9, 2025 – June 11, 2025
HTSAgent-Task-Pritush — GitHub repository
View ProjectData-Anlayst-Agent
June 8, 2025 – June 8, 2025
it can easily analyze any file type and resolve user query about anything related to it
View Projectdynamic-web-clg
April 10, 2024 – May 26, 2024
https://drive.google.com/drive/folders/1XZAgz1QaJ20i88Pz-343H3G-D7gGhwMI?usp=sharing
View ProjectALL-Machine-Learning-Algorithims
January 12, 2023 – January 16, 2024
this comprises of all the ml algos which i have studied
View ProjectCustomer-Segmentation-Project
August 15, 2022 – August 15, 2022
A Segmentation Project based on K-Mean Clusturing
View Projectpython-projects-
January 16, 2022 – January 3, 2023
Projects made on python for better under standing about the python programming language
View ProjectCultural Fit Analysis
The candidate shows initiative through several personal projects, indicating a self-starter attitude. The diversity of projects, though mostly personal and introductory, suggests an eagerness to explore different areas within data science and programming. However, the lack of team-based projects or professional experience makes it difficult to fully assess cultural fit in a collaborative environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights.