Lectures related to High-availability cluster

Compares random and symmetrical graph coloring in terms of cluster colorability and equilibrium.

Explains k-means clustering, assigning data points to clusters based on proximity and minimizing squared distances within clusters.

Graph metrics: Statistical analysis

Explores graph metrics and statistical analysis in network clustering, including ERGMs application in sociology and asymptotics.

Distributed Actors: Principles and Failure Detection

Explores distributed actors, failure detection in clusters, and lifecycle monitoring for distributed fail-over.

Distributed Actors: Cluster Management

Explores distributed actor management in clusters, emphasizing consensus, failure detection, and lifecycle monitoring.

Efficient Data Clustering

Covers efficient data exploitation through clustering methods and the optimization of market returns using asset clustering.

Open-World Semantic Scene Understanding: SCIM

Introduces SCIM for open-world semantic scene understanding through clustering, inference, and mapping.

Advanced Design in Semiconductor Electronics

Explores challenges in advanced semiconductor design, focusing on power efficiency, bandwidth, and volume predictions in computing engines.

Dynamics of Singular Riemann Surface Foliations

Explores the dynamics of singular Riemann surface foliations on compact Kähler manifolds.

K-Means Clustering: Basics and Applications

Introduces K-Means Clustering, a simple yet effective algorithm for grouping data points into clusters.

Observable Universe: Contents and Properties

Explores the 3D distribution of galaxies, galaxy clustering, and the cosmic microwave background, shedding light on the observable universe's contents and properties.

Image Segmentation: K-means and Color Spaces

Explores image segmentation using K-means clustering and discusses the impact of different color spaces.

Tackle the Type I - East Studio

Explores housing typologies through case studies and urban design analysis.

Genomic Data Analysis: Clustering and Survival

Explores genomic data clustering, survival analysis, gene identification, and statistical significance in cancer research.

Clustering Methods: K-means and DBSCAN

Explores K-means and DBSCAN clustering methods, discussing properties, drawbacks, initialization, and optimal cluster selection.

Disaster Risk Reduction: Preparedness & Technology

Delves into disaster risk reduction through preparedness, emphasizing coordination and technology for resilience.