Understanding Data for AI

Data is fuel for AI.

Why Data Matters

AI = Smart only when trained with good data

Bad data = Bad AI
Good data = Good AI

Types of Data

Numbers: Age, price, temperature
Text: Reviews, emails, articles
Images: Photos, X-rays, satellite images
Audio: Voice recordings, music
Video: Movies, surveillance footage

Data Quality

Good Data:

• Accurate
• Complete
• Relevant
• Enough quantity

Bad Data:

• Missing values
• Errors
• Outdated
• Too little

Example

Training AI to predict apartment rent in Chicago:

Good Data: 10,000 apartments with size, location, amenities
Bad Data: 50 apartments with missing information

Data Preparation

1. Collect: Gather data
2. Clean: Remove errors
3. Organize: Structure properly
4. Split: Train data + Test data

Real Example

Netflix has data on:

• What you watched
• When you watched
• What you rated
• What you skipped

This data helps AI recommend shows!

Remember

• More quality data = better AI
• Clean data before using
• Data privacy is important