Linear Algebra: Basic Reflection and Projection Matrices
Learn the basics of Linear Algebra with this series from the Worldwide Center of Mathematics. Find more math tutoring and lecture videos on our channel or at http://centerofmath.org/
From playlist Basics: Linear Algebra
Linear Algebra for Computer Scientists. 12. Introducing the Matrix
This computer science video is one of a series of lessons about linear algebra for computer scientists. This video introduces the concept of a matrix. A matrix is a rectangular or square, two dimensional array of numbers, symbols, or expressions. A matrix is also classed a second order
From playlist Linear Algebra for Computer Scientists
Ch7Pr38: Matrix Representation Theorem
This video answers four questions regarding properties of a linear transformation, its image, rank and nullity. This is Chapter 7 Problem 38 from the MATH1231/1241 Algebra notes. Presented by Dr Thomas Britz from the UNSW School of Mathematics and Statistics.
From playlist Mathematics 1B (Algebra)
Understanding Matrices and Matrix Notation
In order to do linear algebra, we will have to know how to use matrices. So what's a matrix? It's just an array of numbers listed in a grid of particular dimensions that can represent the coefficients and constants from a system of linear equations. They're fun, I promise! Let's just start
From playlist Mathematics (All Of It)
What is a matrix? Free ebook http://tinyurl.com/EngMathYT
From playlist Intro to Matrices
Matrix Addition and Scalar Multiplication
This is the first video of a series from the Worldwide Center of Mathematics explaining the basics of matrices. This video deals with matrix dimensions, matrix addition, and scalar multiplication. For more math videos, visit our channel or go to www.centerofmath.org
From playlist Basics: Matrices
Introduction to Matrices | Geometry | Maths | FuseSchool
Introduction to Matrices | Geometry | Maths | FuseSchool Chances are, you have heard the word “matrices” in a movie. But do you know what they are or what they are used for? Well, “matrices” is plural of a “matrix”. And you can think about a matrix as just a table of numbers, and that’s
From playlist MATHS: Geometry & Measures
Applications in Computer Vision Using Mathematica 10
For the latest information, please visit: http://www.wolfram.com Speaker: Matthias Odisio Wolfram developers and colleagues discussed the latest in innovative technologies for cloud computing, interactive deployment, mobile devices, and more.
From playlist Wolfram Technology Conference 2015
A New Framework for Modeling Brain Information Processing - Nikolaus Kriegeskorte
Nikolaus Kriegeskorte, Programme Leader at the Medical Research Council's Cognition and Brain Sciences Unit in Cambridge, UK, describes a framework for testing such massively multivariate brain-activity data.
From playlist Wu Tsai Neurosciences Institute
NIPS 2011 Sparse Representation & Low-rank Approximation Workshop: For Transform Invariant..
Sparse Representation and Low-rank Approximation Workshop at NIPS 2011 Invited Talk: TILT: For Transform Invariant Low-Rank Structures in Images by Yi Ma, University of Illinois at Urbana-Champaign Abstract: In this talk, we will introduce a fundamental computational tool, namely TIL
From playlist NIPS 2011 Sparse Representation & Low-rank Approx Workshop
AMMI Course "Geometric Deep Learning" - Lecture 1 (Introduction) - Michael Bronstein
Video recording of the course "Geometric Deep Learning" taught in the African Master in Machine Intelligence in July-August 2021 by Michael Bronstein (Imperial College/Twitter), Joan Bruna (NYU), Taco Cohen (Qualcomm), and Petar Veličković (DeepMind) Lecture 1: Symmetry through the centur
From playlist AMMI Geometric Deep Learning Course - First Edition (2021)
Complex Matrices ( An intuitive visualization )
Complex Matrices are not given enough credit for what they do and even when they are used its often introduced as an foreign entity. This video was made to shed light on such a misinterpreted topic. Timestamps 00:00 - Introduction 00:11 - Matrix 00:45 - Complex Number 02:50 - Complex Ma
From playlist Summer of Math Exposition Youtube Videos
Seminar on Applied Geometry and Algebra (SIAM SAGA): Rekha Thomas
Date: Tuesday, November 10 at 11:00am EST (5:00pm CET) Speaker: Rekha Thomas, University of Washington Title: When Two Cameras Meet a Cubic Surface Abstract: The set of images captured by an arrangement of pinhole cameras is usually modeled by the multiview variety. The true set is in f
From playlist Seminar on Applied Geometry and Algebra (SIAM SAGA)
Part 2: The Big Picture of Linear Algebra
MIT A 2020 Vision of Linear Algebra, Spring 2020 Instructor: Gilbert Strang View the complete course: https://ocw.mit.edu/2020-vision YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP61iQEFiWLE21EJCxwmWvvek Multiplication by A transforms the row space to the column space
From playlist A 2020 Vision of Linear Algebra, Spring 2020
Michael Bronstein: "Deep functional maps: intrinsic structured prediction..."
New Deep Learning Techniques 2018 "Deep functional maps: intrinsic structured prediction for dense shape correspondence" Michael Bronstein, USI Lugano, Switzerland /Tel Aviv University, Israel/Intel Perceptual Computing, Israel Abstract: Recently, there has been a keen interest in the co
From playlist New Deep Learning Techniques 2018
Deep Networks from First Principles
The Data Science Institute (DSI) hosted a virtual seminar by Yi Ma from UC Berkeley on May 10, 2021. Read more about the DSI seminar series at https://data-science.llnl.gov/latest/seminar-series. In this talk, we offer an entirely “white box’’ interpretation of deep (convolution) network
From playlist DSI Virtual Seminar Series
So ... What Actually is a Matrix ? : Data Science Basics
What's the best way to think about a matrix for data science? --- Like, Subscribe, and Hit that Bell to get all the latest videos from ritvikmath ~ --- Check out my Medium: https://medium.com/@ritvikmathematics
From playlist Data Science Basics
Lecture 1: A Brief History of Geometric Deep Learning - Michael Bronstein
Video recording of the First Italian Summer School on Geometric Deep Learning, which took place in July 2022 in Pescara. Slides: https://www.sci.unich.it/geodeep2022/slides/Pescara%202022%20-%20Intro.pdf
From playlist First Italian School on Geometric Deep Learning - Pescara 2022
Universality of Random Matrices, Dyson Brownian Motion, and Quantum Unique Ergodicity - H.T. Yau
H. T. Yau Harvard University September 27, 2013 More videos on http://video.ias.edu
From playlist Dreams of Earth and Sky
Math 060 102317 Matrix Representations of Linear Transformations III
Review of the construction of the matrix representation of a linear transformation with respect to bases. Review: matrix representation of a linear transformation between Euclidean spaces with respect to bases (not necessarily the standard bases). Example.
From playlist Course 4: Linear Algebra (Fall 2017)