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unit 2/01_Introduction_to_ML.md

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+# Introduction to Machine Learning
+
+## Supervised Learning
+**Supervised learning** is like teaching a computer with examples. You give the computer inputs (predictors) and the correct answers (targets). The computer learns a "map" or rule to connect the inputs to the outputs.
+
+- **Goal**: Find a model that maps input variables to a target variable.
+- **Example**: Detecting phishing emails.
+  - You show the computer emails with phrases like "You have won million".
+  - You tell the computer these are "Spam".
+  - The computer learns to flag similar new emails as Spam.
+
+### Types of Supervised Learning
+There are two main types of problems:
+1. **Regression**: Predicting a number (e.g., predicting house prices).
+2. **Classification**: Predicting a category or label (e.g., Spam vs Not Spam).
+
+---
+
+## Classification
+In classification, the target variable is a **category** (also called a class label).
+
+**Example**:
+- Labels: Cold, Warm, Hot.
+- The model maps an instance to one of these labels.
+
+### Types of Classification
+
+#### 1. Binary Classification
+There are only **two** possible classes.
+- **Examples**:
+  - Email: Spam or Not Spam.
+  - Loan: Approve or Reject.
+  - Medical: Disease or No Disease.
+  - Exam: Pass or Fail.
+
+#### 2. Multiclass Classification
+There are **more than two** classes.
+- **Examples**:
+  - Digit Recognition: 0, 1, 2, ..., 9 (10 classes).
+  - Fruit: Apple, Banana, Mango, Orange.
+  - Movie Genre: Action, Comedy, Drama, Horror.
+  - Sentiment: Very Negative, Negative, Neutral, Positive, Very Positive.