Covers the training process of a neural network, including feedforward, cost function, gradient checking, and visualization of hidden layers.
Explores parametric spectrum estimation methods, including line and smooth spectra, and delves into heart rate variability analysis.
Introduces a programming course for engineers, emphasizing the importance of mastering multiple languages for future projects.
Covers the basics of working with text files in C programming, including opening, reading, writing, and closing files, with examples and demonstrations.
Introduces functions in Python, covering predefined and user-defined functions, formal and effective parameters, and the importance of docstrings.
Explores nonlinear truss system analysis, covering force-displacement responses, event-to-event principles, and solution algorithms.
