alisongh / siads-696-milestone-ii Goto Github PK

1. Proposal draft (completed)
2. Peer review (completed)
3. Proposal final

1. Frequency
2. Mean and Median values
3. Correlation heatmap

• Normalization

  • log
  • boxcox
  • min-max

• Histograms

• Bar charts

• Line charts

• Heatmap

The pre-processing of house prices is done. Please check alison-sandbox branch

Your project report, as a single PDF document and separate Google Doc link. The Google link should point to the final report. Remember, the project report should be no more than 15 pages. Keep this in mind if you are planning to generate the PDF from a Jupyter notebook. We strongly recommend that you use Google Docs, Word, or some other word processing package to generate your final PDF. The Google doc file that you submit will also be where you receive specific, concrete, written feedback from your assigned project coach at the conclusion of the class. Please, however, allow up to a week to receive this feedback, as instructors are grading multiple dense and complicated project reports.

All source code files/scripts (Python, or any other code) used for your project as a separate zip file.

Working URLs that point to either (a) the actual data/API resources you used or (b) if the datafile is over 10 Mb or not available in file form, create a sample file containing the first 100 records.

1. House price prediction
2. COVID-19 vaccines analysis
3. Stock market prediction

Which factors affect house prices in the US?
Alleviating Supply Constraints in the Housing Market
Housing Prices and Inflation

1. Draft 10/20
2. Proofreading 10/23
3. Final 10/24
4. Portfolio website 10/24

Due 10/3

1. Powerpoint needed for the presentation (<= 2 pages)
2. What is going well? What can be improved? What are you doing next?

due by 10/24

Showcase
https://datapane.com/p/R70Dy7b/reports/
Website

• https://towardsdatascience.com/how-to-easily-build-your-first-machine-learning-web-app-in-python-c3d6c0f0a01c#e14b
• https://towardsdatascience.com/build-a-machine-learning-web-app-in-python-683480acbd37
• https://www.youtube.com/watch?v=xl0N7tHiwlw (29:40) local host
• https://towardsdatascience.com/how-to-easily-build-your-first-machine-learning-web-app-in-python-c3d6c0f0a01c deployed by Heroku
• https://www.youtube.com/watch?v=bluclMxiUkA (Github: https://github.com/bnsreenu/python_for_microscopists)

10/10 Monday

• 12-12:20pm ET
• 12:20-12:40pm ET
• 12:40-1pm ET
• 1-1:20pm ET
• 1:20-1:40pm ET
• 1:40-2pm ET
• 2-2:20pm ET
• 2:20-2:40pm ET
• 2:40-3pm ET

https://peps.python.org/pep-0008/

Join Zoom Meeting
https://umich.zoom.us/j/9195792633?pwd=QXlpWWlJaWVnOHRsYzE5TzRkRDQ5Zz09
Meeting ID: 919 579 2633
Passcode: 591