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Related lectures (32)
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Linear Models for Classification: Part 3
Explores linear models for classification, including binary classification, logistic regression, decision boundaries, and support vector machines.
Raising & Managing Money: Summary
Explores venture financing stages, funding analysis, sources, and burn rate importance.
Optimization in Energy Systems
Explores optimization in energy systems, focusing on decision-making through objective functions and constraints to determine system states.
Likelihood Ratio Test: Detection & Estimation
Covers the likelihood ratio test for detection and estimation in statistical analysis.
Classification Detection
Covers binary hypothesis testing and decision functions in specific scenarios.
Optimization Methods: Theory Discussion
Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.
Nonlinear SVM: Kernels and Dual Optimization
Explores transforming data with nonlinear maps, kernels, dual optimization, and interpreting SVM results.
Introduction to Supervised Learning and Decision Theory
Covers supervised learning, decision theory, risk minimization, and goal achievement.
Data Governance in Urban Settings
Explores data quality, biases in data, and the importance of good governance practices in urban data settings.
Discrete Optimization: Set Covering
MOOC: Optimization: principles and algorithms - Network and discrete optimization
Explores the set covering problem through the example of completing a sticker collection at a minimum cost.
Robust Design: Trade-off Management in Mechanical Development
Emphasizes the importance of managing trade-offs for product robustness in mechanical design, using Multi-objective Monotonicity Analysis for quantitative analysis and systematic redesign efforts.
Optimization and Simulation
Covers the general framework of optimization and simulation, including deterministic control and the optimization problem.
Optimisation Strategies: Energy Systems Modelling and Optimization
Explores solving strategies for energy system optimization problems and different types of optimization approaches.
Linear Classification Models: From Binary to Multiclass
Explores the extension of linear classifiers to handle multiclass problems and compares their performance on various datasets.
Linear Classification: Signed Distance and Perceptron
Explores signed distance, perceptron, logistic regression, cross entropy, and multi-class classification.
Project Management and Risk Analysis
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Explores project management, risk analysis, and multicriteria analysis for decision-making in project selection.
Multi-Criteria Analysis: Investment Choice
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Covers multi-criteria decision analysis for investment choice and sustainability, including challenges in criteria selection and scoring methods.
Concept Selection and Tradespace Exploration
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Covers decision analysis, concept selection methods, non-dominance, and optimization in system design.
Support Vector Machines: Soft Margin SVM
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Introduces Soft Margin SVM, aiming to balance errors and margin width.
Supervised Learning: Formalization and Cost Functions
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Covers the formalism for supervised learning and decision functions in classification problems.
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