A data web application to predict heart disease using Streamlit.
The data is taken from the UCI Machine Learning repository.
These are the setup and concept instructions to be able to follow the project end to end.
- Ensure that you have Git installed on your system. Install instructions here
- If you are using Git and/or Github for the first time, follow this guide to set up the CLI for Github
- Ensure that Anaconda is installed on you system. You can check the setup instructions here
- Ensure that you have Pip installed on your laptop. You can follow the instructions to install it after you have installed Anaconda. If you want to do it independently, use this.
- Create an account on Heroku.
- Install the Heroku CLI.
First you will create an Anaconda virtual environment. To do this first check whether your Conda CLI is working as intended.
$ conda --version
This should show something like:
conda 4.8.5
After this, create a new conda environment by:
$ conda create --name heart-disease-app
Or, you could follow the instructions mentioned here
Check the environment conda
is using by:
conda env list
You should see the *
next to heart-disease-app
.
Next, check whether pip is installed properly using:
$ pip3 --version
This will show something like:
pip 20.2.2 from /Users/Sayar/anaconda3/lib/python3.6/site-packages/pip (python 3/6)
Lastly, ensure Heroku CLI is working properly:
$ heroku --version
Should show something like:
heroku/7.42.5 darwin-x64 node-v12.16.2
Ensure that your Heroku CLI is using the correct account:
$ heroku login
This will prompt you to press any key after which a tab will open on your browser via which you have to authenticate your account. Once this is done, you should see the confirmation of the account display on your terminal with the correct email id.
Next, clone this repository into your local machine using:
$ git clone https://github.com/Sayar1106/Heart-Disease-Web-Application.git
Activate the virtual environment:
$ conda activate heart-disease-app
Next, install the requirements.txt
in the cloned repository. cd
into the source of the repository and do the following:
$ pip3 install -r requirements.txt
This should install all the required libraries for the workshop.
If you have reached this point you can wait until the workshop webinar.
To run the application make sure you are in the project directory:
$ streamlit run app/app.py
This will either automatically open a new tab in the browser or will give you a link to paste onto the browser.
we will be doing this during the session.
Required:
- Python and it's Data Structures.
- Understanding of ML and Data Anlaysis.
Recommended:
- Pandas
- Numpy
- Plotly
- Scikit-learn
Optional
- Shell
I will be using Visual Studio Code for this project because they offer fantastic support for Python and for IPython Notebooks. I will be demoing code in both in an IPython Notebook as well as Python3.
You can install Visual Studio Code here
Feel free to submit pull requests or add issues to the project.