
A mechanical engineering student with a copious interest in data science.
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Competetive-programming-using-Python
June 19, 2021 – June 28, 2021
Competetive-programming-using-Python — GitHub repository
View ProjectFace-count-in-a-image
November 29, 2020 – November 29, 2020
Face-count-in-a-image — GitHub repository
View ProjectInsurance-fraud-prediction
July 26, 2020 – July 26, 2020
Insurance-fraud-prediction — GitHub repository
View ProjectData-Analyst-job-analysis
July 18, 2020 – September 18, 2020
Data-Analyst-job-analysis — GitHub repository
View ProjectCar-price-prediction
July 11, 2020 – August 7, 2020
Car-price-prediction — GitHub repository
View ProjectChurn-prediction-using-ML
July 3, 2020 – May 31, 2021
Churn-prediction-using-ML — GitHub repository
View ProjectAirbnb_newyork_2019
June 3, 2020 – June 14, 2020
Airbnb is an online marketplace for arranging or offering lodging, primarily homestays, or tourism experiences since 2008. NYC is the most populous city in the United States and also one of the most popular tourism and business place in the world.
View ProjectPredicting-compressive-strength-of-concrete
May 26, 2020 – May 27, 2020
Compressive strength or compression strength is the capacity of a material or structure to withstand loads tending to reduce size, as opposed to tensile strength, which withstands loads tending to elongate. compressive strength is one of the most important engineering properties of concrete. It is a standard industrial practice that the concrete is classified based on grades. This grade is nothing but the Compressive Strength of the concrete cube or cylinder. Cube or Cylinder samples are usually tested under a compression testing machine to obtain the compressive strength of concrete. The test requisites differ country to country based on the design code. The concrete compressive strength is a highly nonlinear function of age and ingredients .These ingredients include cement, blast furnace slag, fly ash, water, superplasticizer, coarse aggregate, and fine aggregate.
View ProjectCultural Fit Analysis
The candidate's projects show a strong inclination towards practical data science problems, which aligns with a data scientist role. However, the projects are all personal and lack diversity in terms of team collaboration or industry-specific applications beyond general problem statements. The breadth of skills is focused on Python/Jupyter Notebook for data science, without explicit mention of other tools or methodologies common in a professional data science environment (e.g., MLOps, cloud platforms, advanced SQL, A/B testing).
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's profile primarily lists technical projects without details on collaboration, problem-solving approaches, or communication in a team setting.