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What is Unit-I Machine Learning Basics about?

The document provides an overview of machine learning concepts, including definitions of tasks, performance measures, and types of learning such as supervised, unsupervised, and reinforcement learning. It discusses the importance of generalization, capacity, overfitting, and underfitting, along with techniques like regularization and cross-validation. Additionally, it touches on the no free lunch theorem and the role of hyperparameters in model training and evaluation.

Author

22h51a6710

Language

EN