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A retail company ABC Private Limited wants to understand the customer purchase behaviour (specifically, purchase amount) against various products of different categories. They have shared purchase summary of various customers for selected high volume products from last month.
The data set also contains customer demographics (age, gender, marital status, city_type, stay_in_current_city), product details (product_id and product category) and Total purchase_amount from last month.
Now, they want to build a model to predict the purchase amount of customer against various products which will help them to create personalized offer for customers against different products.
This project analyzes a dataset containing ecommerce product reviews. The goal is to use machine learning models to perform sentiment analysis on product reviews and rank them based on relevance. Reviews play a key role in product recommendation systems.
In this machine learning project, we will implement Back-propagation Algorithm from scratch for classification problems.
The goal of this data science project is to build a predictive model and find out the sales of each product at a given Big Mart store.