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Related lectures (32)

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Kernel Methods: Nonlinear Separation Surfaces

Explores kernel methods for nonlinear separation surfaces using polynomial and Gaussian kernels in Perceptron and SVM algorithms.

Image Processing: Neighborhood Averaging & Gaussian Smoothing

Explores neighborhood averaging, Gaussian smoothing, median filtering, contrast enhancement, and edge detection in image processing.

Image Processing: Smoothing and Filtering

Covers image smoothing, noise reduction, and segmentation techniques using filters and transforms.

Modularity and Abstraction

Explores the principles of modularity and abstraction in computer systems design, emphasizing their role in simplifying complex systems and improving scalability.

Wave Packets and Dispersion

Explores wave packets, dispersion, fast light, and superluminal group speed in optics.

MLE for Gaussian: EMV in Gaussian Model

Discusses Maximum Likelihood Estimation for Gaussian mean and variance, exploring parameter estimation in a Gaussian distribution.

Linear Phase Filters: Step Response and Characteristics

Explores linear phase filters, rise time, Gaussian filters, and rational transfer functions.

Image Filtering: Basics and Techniques

Explores image filtering techniques, including linear and nonlinear filters, for artifact removal and feature enhancement.

Kernels: Nonlinear Transformations

Explores kernels for simplifying data representation and making it linearly separable in feature spaces, including popular functions and practical exercises.

Advanced Structure Discovery: Distance Metrics and Time Series Data

Explores clustering algorithms, distance metrics, and time series data analysis techniques.