Get a room: ML Hackathon
Online 2359 ParticipatingOPENS AT: Jul 22, 04:30 PM
CLOSES ON: Aug 21, 04:30 PM
DURATION: 30 days
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ABOUT CHALLENGE
Problem Statement
Finding the correct property to live in is a crucial task while moving to a new city/location. An inappropriate property can make our life miserable. Can AI help us find better places?
Task
You have given a relevant dataset about various properties in the USA. Your task is to identify the habitability score of the property.
Dataset description
The dataset contains the following files:
- train.csv: 39496 x 15
- test.csv: 10500 x 14
- sample_submission.csv: 5 x 2
The columns provided in the dataset are as follows:
| Column | Description |
| Property_ID | Represents a unique identification of a property |
| Property_Type | Represents the type of the property( Apartment, Bungalow, etc) |
| Property_Area | Represents the area of the property in square feets |
| Number_of_Windows | Represents the number of windows available in the property |
| Number_of_Doors | Represents the number of doors available in the property |
| Furnishing | Represents the furnishing type ( Fully Furnished, Semi Furnished, or Unfurnished ) |
| Frequency_of_Powercuts | Represents the average number of power cuts per week |
| Power_Backup | Represents the availability of power backup |
| Water_Supply | Represents the availability of water supply ( All time, Once in a day - Morning, Once in a day - Evening, and Once in two days) |
| Traffic_Density_Score | Represents the density of traffic on a scale of 1 to 10 |
| Crime_Rate | Represents the crime rate in the neighborhood ( Well below average, Slightly below average, Slightly above average, and Well above average ) |
| Dust_and_Noise | Represents the quantity of dust and noise in the neighborhood ( High, Medium, Low ) |
| Air_Quality_Index | Represents the Air Quality Index of the neighborhood |
| Neighborhood_Review | Represents the average ratings given to the neighborhood by the people |
| Habitability_score | Represents the habitability score of the property |
We challenge you to build a model that successfully predicts the habitability score of a property.
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 Get a room: ML Hackathon
This challenge is designed to help you improve your Machine Learning skills by competing and learning from fellow participants.
Why should you participate?
- To analyze and implement multiple algorithms and determine which is more appropriate for a problem
- To get hands-on experience in Machine Learning problems
Who should participate?
- Working professionals
- Data Science or Machine Learning enthusiasts
- College students (if you understand the basics of predictive modeling)
Tutorials
PRIZES
There are great prizes to be won
First Prize
USD 500
Second Prize
USD 300
Third Prize
USD 200
GUIDELINES
- Your output will be evaluated only for 50% of the test data while the contest is running. Once the contest is over, output for the remaining 50% of the data will be eval...
