ADR Awareness Centre

This lecture overviews Linear Algebra that has many applications in Machine Learning, Computer Vision and Scientific Computing.

This lecture provides an Introduction to Statistics that has many applications in Data Analytics, Machine Learning and Signal Analysis. It covers the following topics in detail: Random Variables. Data Types. Data Sampling.

This lecture overviews Signal Sampling that has many applications in signal acquisition, processing and analysis.

This lecture overviews  Z Transform that has many applications in signal processing and systems theory.

This lecture overviews continuous-time Signals and Systems topics. Continuous-time signals are presented: periodic signals, delta function, unit step signal, exponential signal, trigonometric signals, complex exponential signal.

This lecture overviews Signals and Systems. 1D signals, 2D signals (images), 3D signals (videos, medical volumes) are presented. Multichannel signals come next.