(PP 6.2) Multivariate Gaussian - examples and independence
Degenerate multivariate Gaussians. Some sketches of examples and non-examples of Gaussians. The components of a Gaussian are independent if and only if they are uncorrelated.
From playlist Probability Theory
From playlist Probability Distributions
Probability Distribution Functions and Cumulative Distribution Functions
In this video we discuss the concept of probability distributions. These commonly take one of two forms, either the probability distribution function, f(x), or the cumulative distribution function, F(x). We examine both discrete and continuous versions of both functions and illustrate th
From playlist Probability
(PP 6.1) Multivariate Gaussian - definition
Introduction to the multivariate Gaussian (or multivariate Normal) distribution.
From playlist Probability Theory
Definition of a Discrete Probability Distribution
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Definition of a Discrete Probability Distribution
From playlist Statistics
Random variables, means, variance and standard deviations | Probability and Statistics
We introduce the idea of a random variable X: a function on a probability space. Associated to such a function is something called a probability distribution, which assigns probabilities, say p_1,p_2,...,p_n to the various possible values of X, say x_1,x_2,...,x_n. The probabilities p_i h
From playlist Probability and Statistics: an introduction
Discrete convolutions, from probability, to image processing and FFTs. Help fund future projects: https://www.patreon.com/3blue1brown Special thanks to these supporters: https://3b1b.co/lessons/convolutions#thanks An equally valuable form of support is to simply share the videos. --------
From playlist Prob and Stats
Integral Transforms Lecture 7: The Fourier Transform. Oxford Mathematics 2nd Year Student Lecture
This short course from Sam Howison, all 9 lectures of which we are making available (this is lecture 7), introduces two vital ideas. First, we look at distributions (or generalised functions) and in particular the mathematical representation of a 'point mass' as the Dirac delta function.
From playlist Oxford Mathematics Student Lectures - Integral Transforms
Uniform Probability Distribution Examples
Overview and definition of a uniform probability distribution. Worked examples of how to find probabilities.
From playlist Probability Distributions
Lecture 24 | The Fourier Transforms and its Applications
Lecture by Professor Brad Osgood for the Electrical Engineering course, The Fourier Transforms and its Applications (EE 261). Professor Osgood continues his lecture on linear systems. The Fourier transform is a tool for solving physical problems. In this course the emphasis is on rela
From playlist Lecture Collection | The Fourier Transforms and Its Applications
Why is the most common total of two dice 7? A *Very* Deep Look
Created by Arthur Wesley and Jack Samoncik This video is an informal mathematical proof of the central limit theorem, using the sums of an arbitrary number of dice as an example Music: Chapter 1: https://www.youtube.com/watch?v=eFpJRGB32Ss Chapter 2: https://www.youtube.com/watch?v=g1pS0
From playlist Summer of Math Exposition 2 videos
MIT 6.S191: Convolutional Neural Networks
MIT Introduction to Deep Learning 6.S191: Lecture 3 Convolutional Neural Networks for Computer Vision Lecturer: Alexander Amini January 2022 For all lectures, slides, and lab materials: http://introtodeeplearning.com Lecture Outline - coming soon! Subscribe to stay up to date with new d
From playlist Introduction to Machine Learning
Research: World's fastest fractal generator!
Broadcasted live on Twitch -- Watch live at https://www.twitch.tv/leioslabs
From playlist research
Wolfram Physics Project: Working Session June 9, 2020 [Experimental Math on Multiway Systems | P2]
This is a Wolfram Physics Project working session on experimental mathematics on multiway systems in the Wolfram Model. This is a continuation from this video: https://youtu.be/beRski9cCec Originally livestreamed at: https://twitch.tv/stephen_wolfram Stay up-to-date on this project by vi
From playlist Wolfram Physics Project Livestream Archive
Autoencoders Tutorial | Autoencoders In Deep Learning | Tensorflow Training | Edureka
** AI & Deep Learning with Tensorflow Training: www.edureka.co/ai-deep-learning-with-tensorflow ** This Edureka video of "Autoencoders Tutorial" provides you with a brief introduction about autoencoders and how they compress unsupervised data. You will get detailed information on the diff
From playlist Introduction to Deep Learning
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
Nexus Trimester - László Csirmaz (Central European University, Budapest) 2/3
Geometry of the entropy region László Csirmaz (Central European University, Budapest) February 16, 2016 Abstract: A three-lecture series covering some recent research on the geometry of the entropy region. The lectures will cover: 1) Shannon inequalities; the case of one, two and three va
From playlist Nexus Trimester - 2016 - Fundamental Inequalities and Lower Bounds Theme
Binomial and geometric distributions | Probability and Statistics | NJ Wildberger
We review the basic setup so far of a random variable X on a probability space (S,P), taking on values x_1,x_2,...,x_n with probabilities p_1,p_2,...,p_n. The associated probability distribution is just the record of the various values x_i and their probabilities p_i. It is this probabili
From playlist Probability and Statistics: an introduction