Lectures related to Matplotlib: Types of Graphs

Matplotlib: Overview

Covers a wide range of topics in Matplotlib, including simple plots, subplots, and various types of charts.

Automorphism groups: Trees and Graphs

Explores automorphism groups in trees and graphs, focusing on ends and types of automorphisms.

Automorphism Groups: Trees and Graphs III

Explores automorphism groups of trees and graphs, including actions on trees and group homomorphisms.

Graphs: Properties and Representations

Covers graph properties, representations, and traversal algorithms using BFS and DFS.

Data Visualization: Principles and Practices

Explores data visualization principles, including chart navigation, histograms, scatter plots, box plots, and color usage.

Data Science Visualization with Pandas

Covers data manipulation and exploration using Python with a focus on visualization techniques.

Data Science: Python for Engineers - Part II

Explores data wrangling, numerical data handling, and scientific visualization using Python for engineers.

Data Science Essentials: Pandas, Numpy, Matplotlib

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

NumPy Arrays and Graphical Representations: Introduction

Covers NumPy arrays and their graphical representations using Matplotlib, focusing on array creation, manipulation, and visualization techniques.

Automorphism groups of trees and graphs II

Explores the uniqueness of trees, automorphism groups, Cayley-Abels graphs, and constructing vertex-transitive subgroups with prescribed local actions.

Excel Exercise: Trends

Explores trend analysis in Excel using rent data from 1995 to 2023.

Graphs in Deep Learning: Applications and Techniques

Explores the role of graphs in deep learning, focusing on their structure, applications, and techniques for processing graph data.

Annual Flood Flow Analysis: Gumbel Method

Covers the analysis of annual flood flows using the Gumbel method and practical applications in hydraulic engineering.

Pseudorandomness: Theory and Applications

Explores pseudorandomness theory, AI challenges, pseudo-random graphs, random walks, and matrix properties.

Real Functions: Graphs and Properties

Explores real functions, their graphs, properties, and transformations, including symmetry and surjection.

Data Visualization: Principles and Practices

Emphasizes the importance of data visualization techniques and practices for effective data analysis and communication.

Graphics: MATLAB and Octave for beginners

Introduces 2D graphics using MATLAB and Octave for beginners.

Iterated Integrals: Order and Domains

Explores iterated integrals, order, domains, and symmetrical roles of variables in 2D space.

Data Visualization: Excel Charts

Covers the basics of creating and customizing charts in Excel.

Graphical Models: Representing Probabilistic Distributions

Covers graphical models for probabilistic distributions using graphs, nodes, and edges.