In most cases machine learning gets limited to the same call, fit, predict loop. Whereas ML is actually much more than that. This repository will be a place containing multiple ML projects which involves all the steps starting from data collection to final model deployment. Each of the projects have a separate readme file attached to them which will be explaining the steps to follow for recreating the project on your own system.
- Data collection (present or scraped)
- Data Cleaning
- Data Wrangling
- Data Analysis
- Data Visualization
- EDA
- Outlier Detections
- Creating ML model
- Deployment of the model
More projects coming up soon. Do drop a ⭐ if you like it.