Concept

Operant conditioning

Related lectures (19)

Mastery Learning: Classical Conditioning

Explores mastery learning through classical conditioning, behaviorism principles, and intelligent tutoring systems.

Behaviorism: Classical, Operant Conditioning & Law of Effect

Explores classical and operant conditioning principles, the Law of Effect, and reinforcement concepts.

Mastery Learning and Instructional Design

Explores mastery learning, behaviorism, and instructional design, emphasizing personalized instruction and the effectiveness of Intelligent Tutoring Systems.

Neuroscience: Behavioral Analysis

Explores neuroscience through behavior analysis, focusing on pose estimation and motor control studies.

Shor Algorithm: Quantum Period Finding

Covers the Shor algorithm, focusing on quantum period finding and the use of quantum circuits.

Graph Sketching: Connected Components

Covers the concept of graph sketching with a focus on connected components.

Reinforcement Learning: Reward-based Learning

Explores artificial neural networks, reward information in the brain, animal conditioning, deep reinforcement learning, and a quiz on rewards.

Neural Networks for Action Learning: Brain Implementation Insights

Explores neural networks for action learning and the brain's reinforcement learning implementation.

Thomas algorithm, accuracy of direct methods

Explores the Thomas algorithm for tridiagonal systems and the accuracy of direct methods in numerical computations.

Sparsest Cut: ARV Theorem

Covers the proof of the Bourgain's ARV Theorem, focusing on the finite set of points in a semi-metric space and the application of the ARV algorithm to find the sparsest cut in a graph.

Analog/Digital Systems: Introduction to Signal Conditioning

Introduces analog/digital systems, sensor treatment, signal conditioning, and practical electronic system design.

Pulse Oximetry: Optical Sensors

Explores pulse oximetry principles, optical sensors, SO₂ expression, and calibration techniques in medical instrumentation.

Variational Formulation: Information Measures

Explores variational formulation for measuring information content and divergence between probability distributions.

Diffusion Equation

Covers the Fourier law, heat equation, Righi-Leduc effect, and related experiments.

Conditional Expectation: Definition

Explains conditional expectation, conditioning events, probabilities calculation, and examples with dice and random variables.

Quantum Gravity: Conformal Field Theory Perspectives

Covers the relationship between conformal field theory and Liouville quantum gravity, focusing on correlation functions and the implications of cutting LQG by SLE loops.

Measurement Systems: Principles and Components

Covers the principles and components of measurement systems, including accuracy, uncertainty, and error classification.

Linear Systems: Iterative Methods

Covers iterative methods for solving linear systems, including Jacobi and Gauss-Seidel methods.

Optimization Methods in Machine Learning

Explores optimization methods in machine learning, emphasizing gradients, costs, and computational efforts for efficient model training.