Machine learning — definition?
Data-driven models predicting outcomes.
Features (x) — role?
Input attributes for prediction.
Regression — mechanism?
Predicts continuous numeric values.
Machine learning — defines?
Models that predict outcomes from data.
Features (x) — role?
Input variables for prediction.
Regression — prediction type?
Predicts continuous numerical values.
Supervised vs unsupervised — difference?
Labeled data vs pattern discovery without labels.
Model evaluation — metrics?
Accuracy, MAE, MSE, F1-score.
Neural network — function?
Layered structure for deep learning.
Clustering — type of learning?
Unsupervised grouping based on similarity.
Answer 9 questions on Fundamentals of Machine Learning.
1. What is the primary purpose of a machine learning model?
2. Which of the following best describes the process of training a machine learning model?
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