Covers topics in Quantum Chemistry, including history, tools, color & draw techniques, shapes, and mathematical conversions.
Explores forced external convection correlations and the procedure for solving convection problems, including the comparison of velocity and thermal boundary layers.
Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.
Covers eigenvalues, eigenfunctions, Hermitian operators, and the measurement of observables in quantum chemistry.
Explores parametric spectrum estimation methods, including line and smooth spectra, and delves into heart rate variability analysis.
Covers Gaussian Mixture Models, Denoising, Data Classification, and Spike Sorting using Principal Component Analysis.
