AI in Real Life Cheat Sheet

Key Definitions

• Artificial Intelligence (AI): Simulation of human intelligence processes by machines, especially computer systems. ✅

• Machine Learning (ML): A subset of AI that enables systems to learn from data and improve over time without explicit programming. ✅

• Deep Learning: A type of ML based on neural networks with multiple layers, mimicking human brain processes. ✅

Important Concepts

Applications of AI

• Healthcare: AI used for diagnostics, treatment recommendations, and personalized medicine. ✅

• Finance: Fraud detection, algorithmic trading, and risk management. ✅

• Transportation: Autonomous vehicles and traffic management systems. ✅

AI Ethics

• Bias: AI systems can perpetuate or amplify biases present in training data. ⚠️

• Privacy: Concerns regarding data collection and user consent. ⚠️

Key Formulas

• Accuracy: True positives + True negatives / Total samples ✅

• Precision: True positives / (True positives + False positives) ✅

• Recall: True positives / (True positives + False negatives) ✅

Common Mistakes to Avoid

Common Mistake: Assuming AI can replace human intuition and creativity entirely.

Memory Tricks

Tip: "AI = Analyze & Improve" — remember that AI analyzes data to improve processes.

Key Diagrams

+------------------+
|     AI System     |
+------------------+
|   Data Input      |
|   (Training Data) |
+------------------+
        |
        v
+------------------+
|   Machine Learning|
|   (Model Training)|
+------------------+
        |
        v
+------------------+
|   Output         |
|   (Predictions)  |
+------------------+