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Python developer | Django backend | Data science & research background
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Assessing your cultural and operational fit
Code-Similarity-Analyzer
November 10, 2025 – November 10, 2025
Code-Similarity-Analyzer — GitHub repository
View ProjectLoan_approval
June 17, 2025 – June 21, 2025
This project focuses on building a machine learning model to predict the approval status of loan applications based on applicant information. It explores data preprocessing, visualization, feature engineering, and classification modeling.
View ProjectAI_jobs_prediction
June 9, 2025 – June 15, 2025
A machine learning–powered system for predicting AI-related job trends by analyzing relevant datasets.
View ProjectFuel-Efficiency
May 21, 2025 – May 21, 2025
This project focused on predicting vehicle fuel efficiency using machine learning techniques. It utilizes the classic Auto MPG dataset, which includes various vehicle attributes such as engine size, horsepower, weight, and miles per gallon (MPG).
View ProjectData-Science-Salaries-Prediction
April 2, 2025 – April 2, 2025
This project aims to provide insights into data science salaries in 2023 and develop predictive models to estimate compensation based on various factors.
View ProjectFake_news_prediction
March 24, 2025 – March 27, 2025
A machine learning-based system for detecting fake news by analyzing text content.
View ProjectDisease_Prediction
March 21, 2025 – March 27, 2025
A machine learning-based disease prediction system that analyzes symptoms to predict potential diseases.
View ProjectAccident-prediction
March 5, 2025 – March 17, 2025
This project applies machine learning techniques (multiple classification) to predict the severity of traffic accidents using historical data.
View ProjectMatrix-Operations
January 30, 2024 – April 25, 2024
This C project provides functionality for performing various matrix operations including calculating determinants, inverses, and solving systems of equations.
View ProjectCultural Fit Analysis
The candidate's projects are primarily focused on Data Science and Machine Learning, which aligns with the target role. However, the projects are all personal and lack diversity in team collaboration or real-world business impact. The technologies used are somewhat limited, primarily Jupyter Notebook and Python, with one C++ project and one HTML/Dockerfile project, suggesting a narrow breadth of practical application beyond core ML scripting. The absence of professional experience or education makes it difficult to assess cultural fit comprehensively.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.