Spaces:
Sleeping
Sleeping
| title: Churn Prediction | |
| emoji: 🌖 | |
| colorFrom: yellow | |
| colorTo: red | |
| sdk: gradio | |
| sdk_version: 3.35.2 | |
| app_file: app.py | |
| pinned: false | |
| # Background: | |
| #### Customer attrition, also known as customer churn or customer turnover, is a significant concern for organizations. It refers to the percentage of customers who stop using a company's product or service within a specified timeframe. Understanding customer churn and identifying key indicators can help organizations implement effective retention strategies to mitigate this problem. | |
| ## The Process | |
| ### The procedure begins with exporting the essential items from the notebook, followed by correctly designing an interface, importing the necessary objects for modeling, and then writing the code to process inputs. The procedure can be summarized as follows: | |
| #### - Import machine learning components into the app script. | |
| #### - Create an interface, | |
| #### - Create a function to handle inputs. | |
| #### - Values are passed through the interface. | |
| #### - Restore these values in the backend, | |
| #### - Apply the required processing, | |
| #### - To produce predictions, submit the processed values to the ML model. | |
| #### - Process the acquired predictions and present them on the interface. | |
| # Created by: Jacob. Jaroya | |
| # https://www.linkedin.com/in/jjaroya/ | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |