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Core AI Concepts Flashcards
Microsoft Azure AI Fundamentals AI-900 Flashcards
| Front | Back |
| Define Reinforcement Learning | A type of machine learning where an agent learns to make decisions by receiving rewards or penalties |
| Define Supervised Learning | A type of machine learning where the model is trained on labeled data |
| Define Unsupervised Learning | A type of machine learning where the model identifies patterns and relationships in unlabeled data |
| What are the main types of Machine Learning | Supervised Learning, Unsupervised Learning and Reinforcement Learning |
| What is Accountability in AI | Holding developers and organizations responsible for the outcomes of AI systems |
| What is Anomaly Detection | A method used to identify unusual patterns or outliers in data |
| What is Artificial Intelligence | The simulation of human intelligence in machines that perform tasks typically requiring human intelligence |
| What is Classification | A supervised learning task that assigns a category label to data |
| What is Data Science | An interdisciplinary field focused on extracting insights from data using various techniques |
| What is Deep Learning | A specialized branch of machine learning using neural networks with many layers to analyze complex patterns |
| What is Fairness in AI | Ensuring AI systems provide unbiased results and do not discriminate against certain groups |
| What is Machine Learning | A subset of AI that uses algorithms to allow computers to learn from data and make predictions or decisions |
| What is Regression | A supervised learning task that predicts a continuous value based on input data |
| What is the difference between AI Machine Learning and Deep Learning | AI is the overall concept ML is a subset of AI and Deep Learning is a specialized branch of ML |
| What is Transparency in AI | The ability to understand and interpret how an AI system makes decisions |
Learn the fundamentals of Artificial Intelligence, Machine Learning, and Deep Learning with clear, concise flashcards. Cover key concepts like supervised, unsupervised, and reinforcement learning, as well as fairness, transparency, and accountability in AI. Perfect for beginners or anyone wanting a simple breakdown of core AI principles, tasks, and methods.