Measure Theory 1.1 : Definition and Introduction
In this video, I discuss the intuition behind measures, and the definition of a general measure. I also introduce the Lebesgue Measure, without proving that it is indeed a measure. Email : fematikaqna@gmail.com Code : https://github.com/Fematika/Animations Notes : None yet
From playlist Measure Theory
Measure Theory - Part 3 - What is a measure?
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From playlist Measure Theory
(PP 6.1) Multivariate Gaussian - definition
Introduction to the multivariate Gaussian (or multivariate Normal) distribution.
From playlist Probability Theory
(PP 1.S) Measure theory: Summary
A brief summary of the material from this section, emphasizing probability measures.
From playlist Probability Theory
Percentiles, Deciles, Quartiles
Understanding percentiles, quartiles, and deciles through definitions and examples
From playlist Unit 1: Descriptive Statistics
In this video, the Flipping Physics team discusses the concept of mass and density by comparing the mass and density of steel and wood. The team first addresses the misconception that steel is always more massive than wood, explaining that the mass of an object cannot be determined without
From playlist Fluids
Joe Neeman: Gaussian isoperimetry and related topics III
The Gaussian isoperimetric inequality gives a sharp lower bound on the Gaussian surface area of any set in terms of its Gaussian measure. Its dimension-independent nature makes it a powerful tool for proving concentration inequalities in high dimensions. We will explore several consequence
From playlist Winter School on the Interplay between High-Dimensional Geometry and Probability
Gravitation (3 of 17) Mass vs Weight, An Explanation
Explains the difference between mass and weight. Very important. No they are not the same thing. Mass is a measure of the amount "stuff" something is made of, the amount of atoms for example. Weight is a measure of the force of attraction between two object that have mass. Of course mass
From playlist Gravitation: Orbital Velocity, Orbital Period, Potential Energy, Kinetic Energy, Mass and Weight
01.3 - ISE2021 - How to measure information
Information Service Engineering 2021 Prof. Dr. Harald Sack Karlsruhe Institute of Technology Summer semester 2021 Lecture 1: Information, Natural Language, and the Web 01.3 - How to measure Information - Information according to Information Theory - Random variables and probability mass
From playlist ISE 2021 - Lecture 01, 14.04.2021
Shannon Nyquist Sampling Theorem
Follow on Twitter: @eigensteve Brunton's website: https://eigensteve.com This video discusses the famous Shannon-Nyquist sampling theorem, which discusses limits on signal reconstruction given how fast it is sampled and the frequency content of the signal. For original papers: Shannon
From playlist Sparsity and Compression [Data-Driven Science and Engineering]
Mean v Median and the implications
Differences between the mean and median suggest the presence of outliers and/or the possible shape of a distribution
From playlist Unit 1: Descriptive Statistics
Learning To See [Part 15: Information]
In this series, we'll explore the complex landscape of machine learning and artificial intelligence through one example from the field of computer vision: using a decision tree to count the number of fingers in an image. It's gonna be crazy. Supporting Code: https://github.com/stephencwe
From playlist Learning To See
SHM - 16/01/15 - Constructivismes en mathématiques - Henri Lombardi
Henri Lombardi (LMB, Université de Franche-Comté), « Foundations of Constructive Analysis, Bishop, 1967 : une refondation des mathématiques, constructive, minimaliste et révolutionnaire »
From playlist Les constructivismes mathématiques - Séminaire d'Histoire des Mathématiques
Probability & Information Theory — Subject 5 of Machine Learning Foundations
#MLFoundations #Probability #MachineLearning Welcome to my course on Probability and Information Theory, which is part of my broader "Machine Learning Foundations" curriculum. This video is an orientation to the curriculum. There are eight subjects covered comprehensively in the ML Found
From playlist Probability for Machine Learning
(IC 1.6) A different notion of "information"
An informal discussion of the distinctions between our everyday usage of the word "information" and the information-theoretic notion of "information". A playlist of these videos is available at: http://www.youtube.com/playlist?list=PLE125425EC837021F Attribution for image of TV static:
From playlist Information theory and Coding
Thibault Damour - Relativité Générale et Trous Noirs : un siècle de développements
Conférence donnée devant L'Association des Amis de l'IHÉS à l'IHÉS le 26 novembre 2015. La fin de l'année 2015 marque à la fois le centenaire de l’édification de la théorie de la Relativité Générale par Albert Einstein, et celui de la découverte mathématique (par Karl Schwarzschi
From playlist Évenements grand public
Anil Seth on a New Science of Consciousness | Closer To Truth Chats
Anil Seth, professor of Cognitive and Computational Neuroscience at the University of Sussex, discusses his new theory about how we experience the world and the self. He talks about the "real problem" of consciousness, measuring consciousness, and the brain as a Predictive Perception Machi
From playlist Closer To Truth Chats
Computational Advances in Social Science Experiments
Dr. Lisa Argyle, Assistant Professor of Political Science at Brigham Young University, talks about how experiments can be advanced using computational methods.
From playlist SICSS 2022
More Standard Deviation and Variance
Further explanations and examples of standard deviation and variance
From playlist Unit 1: Descriptive Statistics
Bathroom Quantum Fields and Vacuum Energy
Building a bathroom got me all philosophical. Video contents: 0:00 Intro on Bathroom energy 1:51 About energy conservation 3:38 Wave character of particles/matter 5:06 Concept and value of vacuum energy 11:08 When theory takes a silly turn 12:25 About probability in QM 16:09 What is a meas
From playlist optics