Problem statement
An art exhibitor is soon to launch an online portal for enthusiasts worldwide to start collecting art with only a click of a button. However, navigating the logistics of selling and distributing art does not seem to be a very straightforward task; such as acquiring art effectively and shipping these artifacts to their respective destinations post-purchase.
Task
The exhibitor has hired you as a Machine Learning Engineer for this project. You are required to build an advanced model that predicts the cost of shipping paintings, antiques, sculptures, and other collectibles to customers based on the information provided in the dataset.
Dataset
The dataset consists of parameters such as the artist’s name and reputation, dimensions, material, and price of the collectible, shipping details such as the customer information, scheduled dispatch, delivery dates, and so on.
The benefits of practicing this problem by using Machine Learning techniques are as follows:
We challenge you to build a model that successfully predicts the cost of shipment for the art exhibitor.
Prizes
Considering these unprecedented times that the world is facing due to the Coronavirus pandemic, we wish to do our bit and contribute the prize money for the welfare of society.
Overview
Machine Learning is an application of Artificial Intelligence (AI) that provides systems with the ability to automatically learn and improve from experiences without being explicitly programmed. Machine Learning is a Science that determines patterns in data. These patterns provide a deeper meaning to problems. First, it helps you understand the problems better and then solve the same with elegance.
Here’s presenting HackerEarth’s Machine Learning challenge: Exhibit A(rt)
This challenge is designed to help you improve your Machine Learning skills by competing and learning from fellow participants.
Why should you participate?
Who should participate?
Tutorials