Computational Modeling of Systems

Related lectures (30)

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Explores data manipulation, exploration, and visualization in data science projects using Python.

Covers the basics of MATLAB and includes an exercise session on metabolic modeling.

Explores numerical integration methods and their application in solving differential equations and simulating physical systems.

Covers the design of a differential amplifier with key parameters like gain and bias current.

Covers data wrangling techniques using Hadoop, focusing on row versus column-oriented databases, popular storage formats, and HBase-Hive integration.

Discusses implementing keyboard events, timers, and file management in GTKmm4 applications.

Explores the analysis of structures and mechanisms through a sample problem of opening a box with a string-held lid.

Covers computational methods focusing on paths and strings, including examples of concatenation, regex elements, and string operations.

Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.

Explores data wrangling with Hadoop, emphasizing storage formats and Hive for big data processing.