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https://github.com/shuyib/fl-predict-covid-19
manning.com liveproject. It is in 3 parts to make a personalized prediction whether someone has COVID-19 based on audio data.
https://github.com/shuyib/fl-predict-covid-19
coronavirus covid-19 data-visualization federated-learning graphs-algorithms machine-learning
Last synced: about 2 months ago
JSON representation
manning.com liveproject. It is in 3 parts to make a personalized prediction whether someone has COVID-19 based on audio data.
- Host: GitHub
- URL: https://github.com/shuyib/fl-predict-covid-19
- Owner: Shuyib
- Created: 2022-04-27T09:04:42.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-06-05T07:31:28.000Z (over 1 year ago)
- Last Synced: 2024-04-16T03:50:52.601Z (9 months ago)
- Topics: coronavirus, covid-19, data-visualization, federated-learning, graphs-algorithms, machine-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 1.77 MB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# predict-covid-19
manning.com liveproject. It is in 3 parts to [make a personalized prediction whether someone has COVID-19 based on audio data](https://www.manning.com/liveproject/handling-sensitive-data).
## Part 1: Federated Learning: Handling Sensitive Data
* [x] read and visualize data
* [x] extract features and labels from individuals
* [x] apply logistic regression and decision trees
## Part 2: Federated Learning: Build Network Models for Pandemics
* [x] Build a contact network
* [x] Compute Infection rates
## Part 3: Federated Learning: Personalized Diagnosis of Symptoms
* [x] Create a graph based iterative machine learning model
* [x] Make Federated Learning Workflow
## File structure
Used the `tree` command in bash terminal to create the directory structure below.
.
├── diagnosis-covid-19-sim-data.ipynb - machine learning modeling with graph interaction enrichment.
├── Dockerfile - a big zip file to replicate this project on your computer.
├── EDA-covid-19-sim-data.ipynb - Exploratory data analysis: Data loading, Data glimpses, cleaning and Data visualization.
├── liveProject-reflections.md - What I have learned in this project.
├── Makefile - worflow orchestration tool.
├── math-modelling-covid-19-sim-data.ipynb - modelling simulated data with graphs.
├── Pipfile - similar to the requirements file. But, better.
├── Pipfile.lock - highlights specific python packages and avoids automatically upgrading packages.
├── README.md - current file you/bots are looking at :wave:
└── requirements.txt - has the packages used in this project for those using virtual environments.
0 directories, 10 files
## Docker
Build docker image
```bash
docker build -t fl-predict-covid-19 .
```
Run the Docker image
```bash
docker run -it -p 8888:8888 fl-predict-covid-19:latest
```