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The dataset has 93 features for more than 200,000 products with the Test Data containing 144K rows and Training Data containing 61K rows. This data science project is a supervised , multinomial classification problem. The dataset has a total of 9 possible product lines and the objective is accurately make class predictions on 144,000 unlabeled products based on the 93 features for the products provided in the dataset.
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.
Deep Learning Project using Keras Deep Learning Library to predict the effect of Genetic Variants to enable personalized Medicine.
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.