https://github.com/amenalahassa/women_poverty_insight
International Women's Day Challenge on Zindi: https://zindi.africa/competitions/international-womens-day-challenge
Science Score: 13.0%
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Low similarity (5.4%) to scientific vocabulary
Repository
International Women's Day Challenge on Zindi: https://zindi.africa/competitions/international-womens-day-challenge
Basic Info
- Host: GitHub
- Owner: amenalahassa
- Language: Jupyter Notebook
- Default Branch: master
- Size: 9.11 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
readme.md
About
International Women's Day Challenge on Zindi
This repo contains the code for the International Women's Day Challenge on Zindi. The challenge is to build a predictive model that accurately estimates the % of households per ward that are female-headed and living below a particular income threshold by using data points that can be collected through other means without an intensive household survey like the census.
I first tried to build a model using the data provided in the challenge. And also do some data analysis to understand the data better.
My main intention was to build a model using Tensorflow Decision Forest. But I also tried to build a model using Yggdrasil Decision Forest and Deep Neural Network.
Technologies Used
- Python
- Pandas
- Numpy
- Matplotlib
- Seaborn
- Scikit-learn
- Tensorflow DF
- YDF (Yggdrasil Decision Forest)
Data
The data is provided by Zindi. I can't share the data here. But you can download the data from the Zindi website.
Notebooks
- analysis.ipynb: Data analysis of the provided data and some visualizations.
- tfdf_model.ipynb: Model building using Tensorflow Decision Forest.
- ydf_model.ipynb: Model building using Yggdrasil Decision Forest.
- dnn_model.ipynb: Model building using Deep Neural Network.
Owner
- Name: Konrad Tagnon Amen ALAHASSA
- Login: amenalahassa
- Kind: user
- Location: Québec
- Repositories: 1
- Profile: https://github.com/amenalahassa
👋 I'm an enthusiastic explorer in the realms of AI and machine learning, let's connect and explore how we can innovate together! 🚀
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