Welcome to the 4th Miniproject. We will, once again, practice supervised learning. In addition to previous tasks and challenges, we will deploy our solution to the cloud as an API service. We will practice the following skills:
- Data Preparation
- Feature Engineering
- Supervised Learning
- Pipelines
- Model Persistance
- Flask - building an API
- Deployment to Cloud (AWS)
- complete the instructions in the Project Notebook
- fill our your README with:
- a brief description of the project and its goals (2-3 sentences)
- your hypothesis generation
- a description of what you found while exploring the dataset
- the steps you took to complete the project (simple description of each step and any difficulties it posed)
- your results/link to a demo (how did your model perform? how does the API you created work? (optional) API usage demo)
- brief discussion of challenges you faced in this project (2-4 sentences or list points)
- description what you would do with a bit more time, and brief discussion of potential issues/biases with your model/use case