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Overview
With the onset of Covid-19, waves of relocation, delays in new construction, and transitions to remote working have impacted the property market. With this in mind, RMDS Lab is announcing its next data science competition: Post-COVID California Property Price Trend Prediction. Contestants will be challenged with developing a model in order to predict trends in property prices. A grant of $1,000 will be awarded to the grand prize winner and $500 to the runner up. This quarter’s judges comprise a series of experts in the field of data science, including individuals who hold positions at NASA JPL and the City of Los Angeles.
Everyone who registers for the competition will receive FREE admission to IM Data, and contestants who complete and submit their project will receive a FREE, one-month premium membership to GRMDS.
For contestants outside of the US:
All other contestants:
The competitors need to use the datasets provided to find out the future trends of property prices in California. Through the process of data research, analysis, feature extraction and modelling, competitors should reach some solid and meaningful arguments.
For example, the competitors might wonder:
• Would the price go up for properties with a garage?
• What kind of properties are worth investment?
• Which cities or areas are more favorable to inventors?
• How closely are the property prices related to nearby schools?
• If there is an additional bedroom with other features unchanged, how is the property price going to change?
All perspectives are welcome! Show us your most valuable conclusions.
Ceremony
June 29 at 5 PM Pacific Time (US and Canada)
https://zoom.us/j/96916689103?pwd=MDZjd1RqRWtkT3lDQW0xVzBnWXhSdz09
Passcode: winners
Timeline
The Problem
This data science competition seeks to create an innovative solution to predict property trends. Contestants will be provided with the necessary data.
Dataset Overview
Participants will need to use the dataset provided below to perform their analysis. This dataset contains the property information of 10+ large cities in California, with a focus on Los Angeles, San Diego, San Jose and San Francisco. This dataset is published solely for the use of competition, please do not use it for other purposes.
There is also a recommended page for contestants to get access to some possible related datasets. Participants are encouraged to research and get open data to make their analysis more sensible and innovative.
⚠ You have to sign in to see the recommended page or download the sample dataset. The data would be available for downloading after the competition begins at May 21.
5/26/21 - Competition Dataset has been updated, please download the dataset again.
Download Sample Dataset View Recommended Page
The related datasets include:
- MORTGAGE INTEREST RATE
This dataset contains the average interest rate on a 30-year fixed-rate mortgage in the United States, published by Freddie Mac. - DEMOGRAPHIC DATA
This dataset comprises demographic data like population, age, sex, race and income, published by the US Census Bureau. - CRIME DATA
This page contains the crime data by California cities, published by FBI. - PUBLIC SCHOOLS DATA
The page contains all active, pending, closed, and merged public schools and districts, also contains their corresponding Zip code, published by California Department of Education. - EARTHQUAKES IN CA
This page allows searches of earthquakes by location, time and magnitude, published by the United States Geological Survey.
Resources
RMDS Lab offers our community a variety of educational resources focusing on data science applications and techniques. You may explore the RMDS learning portal containing various data science courses at learn.grmds.org.
Competitors may use the code “COMPETITION2021” to get complimentary access to our online course on Big Data and AI to Improve Competency and Employability.
Below are additional free resources:
If you have any questions regarding access to training materials and want to learn more about RMDS educational resources, you may use the Forum.
Submission Deliverables
- Source code required (Python or R)
- Readme on how to run your code and requirements.txt on your development environment
- Datasets used in .zip folder
- CSV of results
- Technical report in PDF with names of all team members and team name required
- Optional is a working prototype like map, web page, apps
Evaluation
Impact: What useful business insights are acquired from the proposal? How does this submitted model benefit (or cost) businesses, and what actionable steps are recommended to improve their work?
Methodology Validity: Document the methodology, mathematics, and economic principles behind the proposal and provide the references or reasoning for your approach. How is the prediction generated and how are the factors weighted sensible? Are the assumptions and limitations of the methodology clearly outlined with suggestions to improve the proposal? Are the quantitative steps of data ingestion, feature engineering, model architecture, and performance optimization valid? How robust is your model?
Reproducibility: Does the solution use coding best practices with workflows and documentation to reproduce one’s work? Are the data ingress and egress pipelines reproducible? Is there a clear presentation of data science work in the documentation?
Usability: Is the information presented in a way that is actionable? Would a member of the general public understand the model, what it means, and what actions to take?
Ability to Deploy: Whether or not getting access to the data is realistic, computation time, whether or not it is a good fit within the existing system, scalability of the system to take into account new data sources, how often it needs to be maintained, score with feasible suggestions, easy to maintain/update, how much manpower, time, resources need to be allocated to maintain the functionality?
Fair and Ethical Use of Data: Does the solution take into account biases in data? Is the data from open and trusted sources?
Innovation: Will the idea have a big impact? How innovative is the approach, selection and weighting of various factors, or how information is displayed and communicated?
Guidelines
Stage 1: Registration
Participants will register on GRMDS. We will send out a confirmation email to all participants upon successful registration. Once you form your team, one representative from your team must fill out the Team Registration Form. Please note that this competition is open to all participants globally. For any questions you may ask it on the Forum.
Stage 2: Team work and submission
Submissions must include all deliverables and are due Sunday, June 27 11:59 PDT. Please upload all deliverables to the GRMDS. Place the names of all team members and team name on the technical report. Submission by any individual group member will represent the whole team.
Stage 3: Evaluation and Final Presentation
Our expert committee will evaluate all project deliverables and select the finalist teams at the Awards Ceremony. WorldData.AI and RMDS Lab may work with partners to deploy and use the winning models to score risks to guide our communities in the form of alerts accessed via map, website, or app.
Prizes
-
First Place
$1,000 + Certificate
Complimentary six month premium membership at RMDS Lab
-
Second Place
$500 + Certificate
Complimentary six month premium membership at RMDS Lab
-
Rising Star Award
Considerations for internship positions at RMDS Lab + Certificate
Complimentary six month premium membership at RMDS Lab
Winners will also be considered for publishing opportunities with our partners and speaking opportunities at IM Data 2021.
Code of Conduct
The use of data will adhere to ethical use and protection of individual data privacy. Find the Code of Conduct here.
