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13 of 13 terms
Active learning is a machine learning method where models selectively choose data to improve learning efficiency.
Analytical AI analyzes large datasets to discover patterns, generate insights, and support data-driven decision-making.
Artificial intelligence (AI) allows machines to learn from information, identify trends, make decisions, and complete activities that would typically need human intelligence.
Artificial Life studies life-like behaviors using computer simulations, robotics, and AI-based evolutionary systems.
Autonomous decision system uses AI to analyze data and make decisions without human intervention.
Batch processing handles large data sets by processing them in groups at scheduled times, improving efficiency, scalability, and system performance.
Batch size defines how many samples a model processes per iteration, affecting training speed, memory usage, and overall performance.
Bayesian inference combines prior beliefs with new evidence to calculate updated probabilities, improving predictions in machine learning and statistical analysis.
Big Data refers to large, complex datasets processed using advanced tools to extract insights, improve decisions, and drive business innovation.
Backpropagation is a neural network training algorithm that reduces errors by adjusting weights using gradients to improve model accuracy.
A chatbot is software that simulates human conversation automatically.
Cognitive computing uses AI to mimic human thinking, analyze data, learn patterns, and deliver intelligent insights for improved decision-making processes.
A CNN is a deep learning model that analyzes images by detecting patterns, features, and objects through layered neural network architecture.
Artificial Intelligence is the simulation of human intelligence in machines programmed to think and learn.
AI is the broader concept of intelligent machines, while Machine Learning is a subset that enables systems to learn from data.