Machine Learning Overview

Machine Learning Basics

What is Machine Learning?

• Machine Learning is a technique where computers learn from data and make decisions without explicit programming.

• The system improves performance by learning patterns from past data.

Simple Real-World Example

• Email spam detection

• Recommendation systems (YouTube, Netflix)

Basics of Machine Learning

• Learns patterns from historical data

• Improves with more data and experience

Machine Learning vs Traditional Programming

• Traditional Programming:

  • Rules + Data → Output

• Machine Learning:

  • Data + Output → Rules (Model)

Why is Machine Learning Used?

• Automation of tasks

• Prediction of future outcomes

• Pattern detection in large data

Where Machine Learning is Used?

• Daily life:

  • Google search

  • Face unlock

  • Voice assistants

• Industry:

  • Banking (fraud detection)

  • Healthcare (disease prediction)

  • E-commerce (recommendations)

Application Level of Machine Learning

• Recommendation systems

• Spam detection

• Image recognition

• Fraud detection

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Types of Machine Learning

Supervised Learning

• Uses labeled data (input + output)

• Example:

  • Spam vs Not Spam

  • House price prediction

Unsupervised Learning

• Uses unlabeled data (only input)

• Example:

  • Customer segmentation

  • Data clustering

Difference Between Supervised & Unsupervised Learning

• Supervised:

  • Output known

  • Prediction-based

• Unsupervised:

  • Output unknown

  • Pattern discovery

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Machine Learning Workflow

Workflow of Machine Learning

• A step-by-step process to build ML models

Steps in ML Workflow

• Data collection

• Data preprocessing

• Exploratory Data Analysis (EDA)

• Model training

• Testing and prediction

Difference Between Workflow Stages

• Preprocessing → data cleaning

• EDA → data understanding

• Training → learning patterns

• Testing → checking performance

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Python Basics

Variables

• Store data values

• Example: x = 10

Data Types

• int → integers

• float → decimal numbers

• string → text

• boolean → True / False

Python Data Structures

• List → mutable, ordered

• Tuple → immutable, ordered

Operations on Data

• Insert elements

• Delete elements

Operators

• Arithmetic operators

• Comparison operators

• Logical operators

Inbuilt Functions

• len()

• type()

• sum()

• max()

• min()

User Input

• input()

Output

• print()

• Basic formatting