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## 1. Introduction & Machine Learning Basics## What is Machine Learning? * Machine learning is a subset of Artificial Intelligence (AI). * It allows computers to learn from data without being explicitly programmed. * Tom Mitchell's Definition: A computer program learns from experience $E$, with respect to some class of tasks $T$ and performance measure $P$, if its performance at tasks in $T$, as measured by $P$, improves with experience $E$. * Example: A spam filter learns from past emails ($E$), to flag spam ($T$), measured by accuracy ($P$). ## Designing a Learning System Building an ML system follows a specific step-by-step pipeline:    1. Choose the Training Experience: Determine the type of data available (e.g., historical prices, labeled images).    2. Choose the Target Function: Define exactly what needs to be learned (e.g., a function $f: \text{house attributes} \rightarrow \text{price}$).    3. Choose a Representation: Decide how to represent t...

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