E-commerce catalog categorizer

This project is about creating a categorizer, that is, designing a machine learning model so that based on certain features such as "id", "family, "group", etc., it categorizes the entire batch of products of a e-commerce of auto parts. You can check the final web app by clicking the badge down below. Maybe it takes a bit to load the first time because it's dorment at Streamlit services. To test the app, use the CSV file named "data_rya.csv" to make predictions.

Streamlit Share Deployment

Copy this repo to your own personal one

On https://github.com/new, create a new repository
In your terminal, in your home directory, clone the repo
cd into the repository that is created and you should see all the files now.
Then, connect this cloned repo to your new personal repo made in Step 1: git remote set-url origin https://www.github.com/{your-username}/categorizer.git (be sure to change your username and remove the curly braces)
Run git push origin main to push the local repo to remote. You should now see this same code in your personal categorizer repo.

Run Application

Run command in terminal streamlit run app.py (or your app name)
Preview web page in browser '/'

Deploy to Streamlit

Add your app to GitHub. Streamlit Cloud launches apps directly from your GitHub repo, so your app code and dependencies need to be on GitHub before you try to deploy the app.
Create a free account on Streamlit Share.
Create a requirements.txt file with all your non-standard dependencies (based on any libraries you are importing), separated by a newline. In our case, they are Flask w/ a capital F. Note that libraries like os are standard imports, so they don't need to be included.
To deploy an app, click "New app" from the upper right corner of your workspace, then fill in your repo, branch, and file path, and click "Deploy". As a shortcut, you can also click "Paste GitHub URL".
Advanced settings for deployment, If you are connecting to a data source or want to select a Python version for your app, you can do that by clicking "Advanced settings" before you deploy the app.
Your app is now deploying and you can watch while it launches. Most apps take only a couple of minutes to deploy, but if your app has a lot of dependencies it may take some time to deploy the first time. After the initial deployment, any change that does not touch your dependencies should show up immediately.
Once your app URL it's ready, that's it — you're done! Your app now has a permanent URL that you can share with others. Congrats!

Built With

Python - Programming language
Pandas - Data manipulation python library
Sklearn - Machine learning python library
Streamlit - Web app framework

Author

Maximiliano Diaz Battan

maxidiazbattan / streamlit-categorizador-RepuestosYa