Bro, think of normalization like leveling a playing field. what does normalize data mean? It’s taking your wild, uneven data and taming it into a consistent range.
Why? Because ML models are dumb. If Feature A is 0-1000 and Feature B is 0-1, the model might think A is 1000x more important. Nope.
How? Min-max for simplicity, z-score if your data’s all over the place. Check out Kaggle notebooks—tons of examples with real datasets.
Why? Because ML models are dumb. If Feature A is 0-1000 and Feature B is 0-1, the model might think A is 1000x more important. Nope.
How? Min-max for simplicity, z-score if your data’s all over the place. Check out Kaggle notebooks—tons of examples with real datasets.