There is considerable ambiguity about the concepts of machine learning methodologies and best practices in its implementation among the budding data scientists. This repository consists of simplest possible step-by-step demonstration of solving a real-world problem using linear regression method. It will explain end to end process from data analysis to actual predictions.
- Google Stock data downloaded from renowned website Quandl
- Data collection from online source
- Data wrangling
- Data visualization
- Feature engineering
- Build a linear regression ML model
- Data separation (training data | test data)
- Train the ML model
- Pickle the trained model
- Quantify the accuracy of ML model
- Predictions using ML model
- Visualize predicted data