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Machine Learning Classification Project: Predicting Customer Next Order
In this project, I am going to explain Machine Learning Classification Algorithms and applying these algorithms to instacart dataset. Before writing my post, i would like to share my Github repo, if you interest in, you can find Jupyter Notebook codes.
Classification
Classification is the process of predicting the class with your input data. There are mostly two types of classification in Machine Learning Algorithms, one is supervised learning other is unsupervised learning. In briefly, if your dataset includes your target (label) features and you are going to predict these target, this means supervised learning. If your dataset doesn’t include target (label) feature, this means unsupervised learning.
In this post, I am going to apply supervised learning because I try to predict a purchase that customer will reorder.
Dataset
I am going to use Instacart dataset from Kaggle. Instacart is an American company that operates a grocery delivery and pick-up service in the United States and Canada with headquarters in San Francisco. The company offers service via a website and mobile app in 5,500 cities in all 50 U.S. states and Canadian provinces in partnership with over 350 retailers that have more than 25,000…