What are Connected Graphs? | Graph Theory
What is a connected graph in graph theory? That is the subject of today's math lesson! A connected graph is a graph in which every pair of vertices is connected, which means there exists a path in the graph with those vertices as endpoints. We can think of it this way: if, by traveling acr
From playlist Graph Theory
If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.
From playlist LinkedIn
How to Become a Better Collaborator
In this video, you’ll learn tips and strategies for better collaboration. Visit https://edu.gcfglobal.org/en/creativity/how-to-become-a-better-collaborator/1/ for more information. We hope you enjoy!
From playlist Creativity
Clustering Coefficient Code - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
We will look at the fundamental concept of clustering, different types of clustering methods and the weaknesses. Clustering is an unsupervised learning technique that consists of grouping data points and creating partitions based on similarity. The ultimate goal is to find groups of simila
From playlist Data Science in Minutes
this a brief high-level overview of graph databases using only an ipad. in this video we discuss what a graph database is and how it differs from relational databases. this also looks at high level use cases.
From playlist graph databases
If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.
From playlist Networking
Graph Neural Networks, Session 2: Graph Definition
Types of Graphs Common data structures for storing graphs
From playlist Graph Neural Networks (Hands-on)
Clustering Coefficient - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
Lecture 6. Personalization. Recommender systems
Data Science for Business. Lecture 6 slides: https://drive.google.com/file/d/1Rlyy6uiKsgWo8GDjOQ4Yk4WuOR5xsUQd/view?usp=sharing
From playlist Data Science for Business, 2022
Stefania Ebli (8/29/21): Simplicial Neural Networks
In this talk I will present simplicial neural networks (SNNs), a generalization of graph neural networks to data that live on a class of topological spaces called simplicial complexes. These are natural multi-dimensional extensions of graphs that encode not only pairwise relationships but
From playlist Beyond TDA - Persistent functions and its applications in data sciences, 2021
DSI | Hypergraphs and Topology for Data Science | By Emilie Purvine
Data scientists and applied mathematicians must grapple with complex data when analyzing complex systems. Analytical methods almost always represent phenomena as a much simpler level than the complex structure or dynamics inherent in systems, through either simpler measured or sampled data
From playlist DSI Virtual Seminar Series
Reproducible science with the Renku platform- Sandra Savchenko-de Jong (Swiss Data Science Center)
Sandra Savchenko-de Jong offers an overview of Renku, a highly scalable and secure open software platform developed by the Swiss Data Science Centre (a collaboration between ETH Zurich and EFPL) that is designed to make (data) science reproducible, foster collaboration between scientists,
From playlist JupyterCon in New York 2018
Lior Rokach - Recommender Systems: Twenty years of research
https://indico.math.cnrs.fr/event/3475/attachments/2180/2560/Rokach-GomaxSlides.pptx
From playlist Google matrix: fundamentals, applications and beyond
CCHF-VS 3.4 | Prof. Itami: Creation of New Carbon Materials by C–H Functionalization
Watch Prof. Ken Itami guide us through the C–H Functionalization techniques that are being developed to stitch together novel carbon materials
From playlist CCHF Virtual Symposia
The Collapse of Viruses: Graph-Based Percolation Theory in the Wolfram Language
Graph-based percolation theory may be done in the Wolfram Language, here to aid in the understanding of viruses, their disassembly and eventual collapse. Capsids are protein nanocontainers that store and protect a virus’s genetic material in transit between hosts. Capsids consist of hundre
From playlist Wolfram Technology Conference 2020
Clustering Coefficient Quiz - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
CERIAS Security: Safely Analyzing Sensitive Network Data 1/6
Clip 1/6 Speaker: Gerome Miklau · University of Massachusetts, Amherst Our recent work investigates the properties of a network that can be accurately studied without threatening the privacy of individuals and their connections. We adopt the rigorous condition of differential privacy, an
From playlist The CERIAS Security Seminars 2009