Fundamental Concepts in AI
- Algorithms: Step-by-step instructions that AI models follow to analyze data and make predictions.
- Neural Networks: Systems inspired by the human brain that can recognize complex patterns, essential for deep learning.
- Supervised Learning: Training AI with labeled data, where the correct answers are provided.
- Unsupervised Learning: Training AI with unlabeled data to find hidden patterns or groupings.
- Reinforcement Learning: Teaching AI through trial and error, rewarding correct actions to improve performance over time.
- Bias & Ethics: Ensuring AI systems are fair, unbiased, and used responsibly to benefit society.