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Predict the Introverts from the Extroverts using the [Introverts vs Extroverts dataset](https://www.kaggle.com/datasets/rakeshkapilavai/extrovert-vs-introvert-behavior-data/data).
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Predict the Introverts from the Extroverts using the [Introverts vs Extroverts dataset](https://www.kaggle.com/datasets/rakeshkapilavai/extrovert-vs-introvert-behavior-data/data) collected through Google Forms as part of a college research project exploring personality traits and behavioral tendencies among students.
Predict the categorical academic risk assessment for each student using data from the [Predict Students' Dropout and Academic Success dataset](https://archive.ics.uci.edu/dataset/697/predict+students+dropout+and+academic+success).
Predict the probability of various defects on steel plate. The dataset for this competition (both train and test) was generated from a deep learning model trained on the[Steel Plates Faults dataset](https://archive.ics.uci.edu/dataset/198/steel+plates+faults).
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Predict the probability of defects on steel plate using[Steel Plates Faults dataset](https://archive.ics.uci.edu/dataset/198/steel+plates+faults).
Predict the quality of wine using the given data. The dataset for this competition (both train and test) was generated from a deep learning model trained on the[Wine Quality dataset](https://www.kaggle.com/datasets/yasserh/wine-quality-dataset).
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Predict the quality of wine using the physicochemical of Portuguese vinho verde samples:[Wine Quality dataset](https://www.kaggle.com/datasets/yasserh/wine-quality-dataset).
Predict the probability for the target Class for each id in the test set using synthetic data from the[Credit Card Fraud Detection dataset](https://www.kaggle.com/datasets/mlg-ulb/creditcardfraud).
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Predict credit card fraud using data collected from the European cardholder transactions in September 2013:[Credit Card Fraud Detection dataset](https://www.kaggle.com/datasets/mlg-ulb/creditcardfraud).
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