Spaces:
Runtime error
Runtime error
File size: 2,943 Bytes
fcd66fa |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 |
# Machine-learning model Dockerized FastAPI Sepsis Prediction
## Description
Welcome to the Sepsis Prediction FastAPI application!
This application allows you to predict sepsis in patients using a machine-learning model.
## Introduction
In this project, we'll develop a FastAPI web application that predicts whether a patient has sepsis based on various medical attributes.
## Setup
Install the required packages to be able to run the evaluation locally.
You need to have [`Python 3`](https://www.python.org/) on your system (**a Python version lower than 3.10**). Then you can clone this repo and being at the repo's `root :: repository_name> ...` follow the steps below:
- Windows *(Python should be added to the Path variable of environment)*:
python3 -m venv venv; venv\Scripts\activate; python -m pip install --upgrade pip; python -m pip install -r requirements.txt
- Linux & MacOs:
python3 -m venv venv; source venv/bin/activate; python -m pip install --upgrade pip; python -m pip install -r requirements.txt
The both long command-lines have a same structure, they pipe multiple commands using the symbol **;** but you may manually execute them one after another.
1. **Create the Python's virtual environment** that isolates the required libraries of the project to avoid conflicts;
2. **Activate the Python's virtual environment** so that the Python kernel & libraries will be those of the isolated environment;
3. **Upgrade Pip, the installed libraries/packages manager** to have the up-to-date version that will work correctly;
4. **Install the required libraries/packages** listed in the `requirements.txt` file so that it will be allow to import them into the python's scripts and notebooks without any issue.
#### Getting Started
To run this application, follow these steps:
- Clone the Repository: Clone this repository to your local machine.
- Navigate to the Directory: Open a terminal and navigate to the cloned repository directory.
- Install Docker: Ensure that you have Docker installed on your machine.
- Build the Docker Image
- Run the dockeer image using the following command:
*docker build -t ml-sepsis-prediction-app .*
Run the Docker Container: Once the image is built, run the Docker container using the following command:
*docker run -p 8000:8000 ml-sepsis-prediction-app*
## Summary
| Project's Name | Published Article | Deployed App |Docker Hub Repository|
|:--------------:|:--------------:|:--------------:|:--------------:|
| Sepsis Prediction Using Fastapi|[Project Article](https://www.linkedin.com/pulse/classification-machine-learning-fastapi-sepsis-imanirakarama-4ivkf/) | [Deployed App]()| [Docker Hub](https://hub.docker.com/repository/docker/imalexianne/machine_learning_sepsis_predicion_fastapi/general)
## Author
Alexianne Imanirakarama
email:<[email protected]>
My LinkedIn:<https://www.linkedin.com/in/imalexianne>
|