RAMYASREE POLARPU
A dataset is a collection of data used to train, test, and evaluate a machine learning model. It usually looks like a big table (rows = examples, columns = features).
Why Does Data Matter in ML?
1.Learning Happens from Data
ML models learn patterns from examples, not from rules like traditional programming.
“Garbage in = Garbage out” — if the data is bad, the model will be bad.
2.Better Data = Better Accuracy
The quality, quantity, and diversity of data directly affect how accurate and fair the model will be.
3.Testing Needs Data Too
You need separate data to test whether your model is truly learning — and not just memorizing the training examples.
4.Bias and Fairness
Biased data leads to biased decisions. For example, if a hiring model is trained only on male resumes, it may ignore female applicants unfairly.