Oluwadara Adepoju (@Oluwadara-Adepoju)
github

Oluwadara-Adepoju

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  • Global Rank 2,218,872 (Top 77 %)
  • Followers 6
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  • Registered about 4 years ago
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  • Location 🇳🇬 Nigeria
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Top repositories

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AutoInland-Vehicle-Insurance

The objective is to develop a predictive model that determines if a customer will submit a claim within 3 months from their first transaction.is to develop a predictive model that determines if a customer will submit a claim within 3 months from their first transaction.
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WiD-Datathon-2020

he WiDS Datathon 2022 focuses on a prediction task involving roughly 100k observations of building energy usage records collected over 7 years and a number of states within the United States. The dataset consists of building characteristics (e.g. floor area, facility type etc), weather data for the location of the building (e.g. annual average temperature, annual total precipitation etc) as well as the energy usage for the building and the given year, measured as Site Energy Usage Intensity (Site EUI). Each row in the data corresponds to the a single building observed in a given year. Your task is to predict the Site EUI for each row, given the characteristics of the building and the weather data for the location of the building. You are provided with two datasets: (1) the training dataset where the observed values of the Site EUI for each row is provided and (2) the test dataset where we withhold the observed values of the Site EUI for each row. To participate in the Datathon, you will submit a solution file containing the predicted Site EUI values for each row in the test dataset. The predicted values you submit will be compared against the observed Site EUI values for the test dataset and this will determine your standing on the Leaderboard during the competition as well as your final standing when the competition closes.
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