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I have extensive experience in data management and data processing. Over the past few years I saw the data management technology transition into the Big Data ecosystem and I needed to follow suit. I... Read More
I have 11 years of experience and work with IBM. My domain is Travel, Hospitality and Banking - both sectors process lots of data. The way the projects were set up and the mentors' explanation was... Read More
A retail company “ABC Private Limited” wants to understand the customer purchase behavior (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 black friday data hack dataset 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 machine learning model to predict the purchase amount of customer against various products which will help them to create personalized offer for customers against different products.
The goal of this machine learning project is to predict which products existing customers will use next month based on their past behaviour and that of similar customers.
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.
Build a predictive model to correctly classify products between 9 product categories (fashion, electronics, etc.) using the Otto Group dataset.