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Predicting Student Performance and Purchases by kethinenibhuvan2004 is a document available to read on EtoBox.

The document outlines various machine learning tasks using linear and logistic regression, including predicting student marks based on study hours, predicting pass/fail status from study hours, and predicting purchase decisions based on customer age. It also discusses using the MNIST dataset for predicting average pixel brightness, classifying images as bright or dim, and determining if an image is the digit

Author
kethinenibhuvan2004
Language
EN