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The inputs include objective tests (e.g. PH values) and the output is based on sensory data (median of at least 3 evaluations made by wine experts). Each expert graded the wine quality between 0 (very bad) and 10 (very excellent). The objective is to predict the wine quality classes correctly.
In this machine learning project, you will build a model to predict the purchase amount of customer against various products which will help the company create personalized offer for customers against different products.
In this machine learning project, we will use binary leaf images and extracted features, including shape, margin, and texture to accurately identify plant species using different benchmark classification techniques.
In this project, we will automate the loan eligibility process (real-time) based on customer details while filling the online application form.