This repo contains Project-03 data and solution at Istanbul Data Science Academy. Project-03 is about Classification of Instacart Dataset.
Classification in machine learning and statistics is a supervised learning approach in which the computer program learns from the data given to it and make new observations or classifications.
Classification is a process of categorizing a given set of data into classes, It can be performed on both structured or unstructured data. The process starts with predicting the class of given data points. The classes are often referred to as target, label or categories.
The classification predictive modelling is the task of approximating the mapping function from input variables to discrete output variables. The main goal is to identify which class/category the new data will fall into. (Edureka)
Finding customer behaviour by using market basket analysis techniques and try to predict next order.
- CSV to PostgreSQL
- Join Tables
- Feature Engineering
- Connect PostgreSQL to Pandas
- Exploratory Data Analysis
- Applying RFM Algorithm
- Determining LCV
- Predicting Reorder Product
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 grocery stores including Albertsons, Aldi, Big Lots, C&S Wholesale Grocers, Costco, CVS Health, Eataly, Price Chopper, H-E-B, Kroger, Loblaw Companies, Petco, Publix, Safeway Inc., Sam's Club, Sprouts Farmers Market, Staples U.S., Target Corporation, Total Wine & More, and Wegmans. (Wikipedia)
Data obtained from Kaggle Instacart https://www.kaggle.com/c/instacart-market-basket-analysis