Lectures related to Five-number summary

Introduces Pandas, Numpy, and Matplotlib for data analysis and visualization in Python.

Covers energy loss in plasma due to impact parameter intervals and Debye screening effects.

Covers inference engines based on resolution, Horn clauses, filtering, and unification in artificial intelligence.

Covers fundamental concepts in probability and statistics, emphasizing data analysis techniques and statistical modeling.

Covers the concept of equivalent formulation in constrained optimization and explores the tangent cone.

Covers PAL, GAL, CPLD, and the transition to FPGAs using HDLs.

Explores FPGA architecture, including LUTs and routing arrays, scalability, and placement challenges.