Developing a Model: Simple Example

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Related lectures (24)

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Software Correctness: Testing and Verification

Explores software correctness through testing, verification, property-based fuzzing, and dynamic information flow control.

What is Formal Verification?

Introduces formal verification and its advantages over traditional testing methods, discussing automated theorem proving and compiling correctness statements into verification conditions.

Data Integration & Cleaning: Expert Matching & Entity Recognition

Covers data integration, expert matching, entity recognition, performance, scalability, stream data management, tensor decomposition, and concept drift detection.

Discrete choice and machine learning: two complementary methodologies

Explores discrete choice and machine learning as complementary methodologies, discussing supervised learning, model advantages, pitfalls, aggregation bias, probabilistic classification, and panel data.

Data Validation Model: Building and Running

Covers the ValiModeller user's guide, focusing on building and running data validation models.

Prediction Tests

Discusses predicting future behavior, identifying outliers, and improving model specification.

Business-IT Alignment: Requirements Management & RPA

Covers business/IT alignment, requirements management, and an introduction to Robotic Process Automation.

Topographic Mapping & GLM I

Introduces topographic brain mapping, auditory pathways, motor cortex organization, and the General Linear Model for fMRI data analysis.

Urban Infrastructure: Planning and Development

Explores urban infrastructure planning, development models, and challenges of urban growth.

CleanCloud Project Overview: Transitioning to a Post-Fossil Era

Outlines the CleanCloud project, focusing on aerosol-cloud interactions and climate transition to a post-fossil regime.