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GitHub / lamdavid759 / Identifying-Outliers-in-California-High-Schools
TDI Capstone Project using machine learning to predict various California HS metrics and identify outliers in performance.
Stars: 0
Forks: 0
Open Issues: 0
License: None
Language: Jupyter Notebook
Repo Size: 64.4 MB
Dependencies:
32
Created: almost 2 years ago
Updated: over 1 year ago
Last pushed: over 1 year ago
Last synced: about 1 year ago
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Dependencies
requirements.txt
pypi
- altair ==4.2.0
- attrs ==22.1.0
- contourpy ==1.0.6
- cycler ==0.11.0
- ediblepickle ==1.1.3
- entrypoints ==0.4
- fonttools ==4.38.0
- geographiclib ==2.0
- geopy ==2.3.0
- importlib-resources ==5.10.1
- jinja2 ==3.1.2
- joblib ==1.2.0
- jsonschema ==4.17.3
- kiwisolver ==1.4.4
- markupsafe ==2.1.1
- matplotlib ==3.6.2
- numpy ==1.23.5
- packaging ==22.0
- pandas ==1.5.2
- pillow ==9.3.0
- pkgutil-resolve-name ==1.3.10
- pyparsing ==3.0.9
- pyrsistent ==0.19.2
- python-dateutil ==2.8.2
- pytz ==2022.6
- scikit-learn ==1.2.0
- scipy ==1.9.3
- seaborn ==0.12.1
- six ==1.16.0
- threadpoolctl ==3.1.0
- toolz ==0.12.0
- zipp ==3.11.0