overview

Machine Learning Process

1. Data Pre-Processing
   • import data
   • clean data
   • split data trainig and testing
   • feature scailing
     • normalization: \(\frac{x - min(x)}{max(x) - min(x)}\)
     • standardization: \(\frac{x - μ}{σ}\)
2. Modeling
   • build / train model
   • make predictions
3. Evaluation
   • calculate performance metrix
   • make a verdict