Gender Prediction Using Mobile App Data

Written by sagol | Published 2021/06/18
Tech Story Tags: machine-learning | data-science | datasets | mobile-apps | python | catboost | eda | exploratory-data-analysis

TLDR The data is a list of users, installed applications, user gender, and statistics on the gender distribution for apps. I have developed a fascinating dataset with users and installed apps. The data shows that women are less likely to indicate their gender in the app’s settings. I will assume that the quality can be increased by tuning the hyperparameters, let it be the homework of the algorithm. I chose the free library for open-source boosting on the source library for the decision-making.via the TL;DR App

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Written by sagol | 22+ years of experience in creating software products in various positions.
Published by HackerNoon on 2021/06/18