AI
Machine Learning & Deep Learning – Data and Math Representation
1. Artificial Intelligence (AI)
Definition:
Artificial Intelligence is the field where machines are designed to simulate human thinking—such
as learning, reasoning, and decision-making.
2. Machine Learning (ML)
Definition:
Machine Learning is a subset of AI in which computers learn patterns from data and make
decisions without being explicitly programmed.
Core Logic:
Traditional Programming:
→
Rules + Data Output
Machine Learning:
→
Data + Output Rules (Model)
Main Types of ML:
1. Supervised Learning – Data + correct answers (labels)
2. Unsupervised Learning – Only data, no labels
3. Reinforcement Learning – Learning through reward and punishment
3. Deep Learning (DL)
Definition:
Deep Learning is an advanced part of Machine Learning that uses multi-layered neural networks to
learn complex patterns automatically.
Key Idea:
Deep Learning = Neural Networks + Many Hidden Layers
Structure:
Machine Learning & Deep Learning – Data and Math Representation
1. Artificial Intelligence (AI)
Definition:
Artificial Intelligence is the field where machines are designed to simulate human thinking—such
as learning, reasoning, and decision-making.
2. Machine Learning (ML)
Definition:
Machine Learning is a subset of AI in which computers learn patterns from data and make
decisions without being explicitly programmed.
Core Logic:
Traditional Programming:
→
Rules + Data Output
Machine Learning:
→
Data + Output Rules (Model)
Main Types of ML:
1. Supervised Learning – Data + correct answers (labels)
2. Unsupervised Learning – Only data, no labels
3. Reinforcement Learning – Learning through reward and punishment
3. Deep Learning (DL)
Definition:
Deep Learning is an advanced part of Machine Learning that uses multi-layered neural networks to
learn complex patterns automatically.
Key Idea:
Deep Learning = Neural Networks + Many Hidden Layers
Structure:
