18 Questions
In 1986, who popularized backpropagation for training multi-layer networks?
Rumelhardt, Hinton, Williams
Who were the individuals responsible for the 'cells that fire together wire together' learning rule?
Hebb
Who applied convolutional neural networks to recognizing handwritten digits for USPS in 1998?
LeCun
Which algorithm showed that linear models could not solve XOR, leading to a decline in neural nets research in 1969?
Perceptron algorithm
In which year did AlexNet obtain huge gains in object recognition, transforming the computer vision community?
2016
Which AI subfield is primarily concerned with teaching computers to learn from data without explicit programming?
Machine Learning (ML)
What concept goes back as far as Gauss and Legendre and is at the heart of machine learning?
Principle of least squares for linear regression
What are some common applications of Machine Learning (ML)?
Predictions, pattern recognition, and decision-making
In which AI subfield would you find applications like image recognition, object detection, and facial recognition?
Computer Vision
Which AI subfield combines AI with mechanical systems to create intelligent machines for physical tasks?
Robotics
Which AI subfield focuses on enabling computers to understand, interpret, and generate human language?
Natural Language Processing (NLP)
What are computer programs designed to mimic the decision-making abilities of human experts in a specific domain called?
Expert Systems
Which of the following was developed by Fisher in the field of statistics?
Classification (Linear Discriminant Analysis)
Which paradigm in machine learning was influenced by statistical learning theory and optimization?
Support Vector Machines (SVMs)
Which AI approach is known for its mathematical rigor and providing methods for understanding AI systems trained with real-world data?
Statistical AI
Which AI approach took a top-down strategy and initially failed to meet its original goal?
Symbolic AI
Which AI approach offered a class of models capable of solving complex problems and started with simple perceptual tasks?
Neural AI
What is the primary difference between Neural AI and Symbolic AI approaches?
Neural AI takes a bottom-up approach, starting with simple tasks, while Symbolic AI takes a top-down approach
Explore the development of linear discriminant analysis by Fisher in statistics, and learn about its overlap with the realms of machine learning, statistics, and data mining. Compare linear discriminant analysis with Bayesian networks and Support Vector Machines in the context of machine learning paradigms.
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