hackforla / hackforla/lucky-parking

Create parking score for real estate price prediction

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#212 5 comments 0 reactions 0 assignees View on GitHub
complexity: large feature: new feature ideation missing: milestone role: data scientist size: 13+pt
Dominant language
Jupyter Notebook
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37
Forks
60
Avg merge
13h 32m
Merged PRs (30d)
5

Description

### Overview
Real estate price prediction is a huge application of machine learning. Although it has been getting better recently, it still is often times wildly off. A lot of this has to do with their algorithm simply not taking all the relevant information into account. Local parking conditions do have an impact on people's quality of life and could be factored into a house price estimation.

### Action items
- [ ] Scraping real estate data
- [ ] EDA
- [ ] Feature engineering
- [ ] Create new features based on coordinates and local parking statistics
- [ ] Examine correlations with housing closing price around same date of sale
- [ ] Create and evaluate models
- [ ] Create Flask API
- [ ] Look into scaling it

### Resources/Instructions
Confer with Greg

Contributor guide

Open the contributing guide

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