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Сreating a streamlit application for EDA and predicting the behavior of bank customers

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data-silence/banks-clients

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https://banks-clients.streamlit.app/

This work is a study of banking users and predicting their behavior using machine learning techniques.

The project is designed to demonstrate some skills in data-science: conducting Exploratory Data Analysis, building predictive machine learning models, formalizing the results of the research in the form of a web service using Streamlit and FastApi framework.

In essence, a product problem was solved using machine learning methods, the solution was formalized and brought to the production stage.

This project has created as part of the "Линейные модели и их презентация" course offered by AI Education.

Эта работа представляет собой исследование банковских пользователей, а также прогнозирование их поведения с помощью методов машинного обучения.

Проект разработан для демонстрации некоторых навыков в области data-science: проведение Exploratory Data Analysis, построение предсказательных моделей машинного обучения, оформление результатов исследования в виде веб-сервиса при помощи Streamlit и фреймворка FastApi.

По сути была решена продуктовая задача методами машинного обучения, решение было оформлено и доведено до стадии продакшена.

License

This project is licensed under the MIT license. For more information, see the LICENSE file.

Contacts

For any questions you may have, please contact us by enjoy@data-silence.com or telegram @data-silence

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Сreating a streamlit application for EDA and predicting the behavior of bank customers

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