In probability theory and statistics, the half-logistic distribution is a continuous probability distribution—the distribution of the absolute value of a random variable following the logistic distribution. That is, for where Y is a logistic random variable, X is a half-logistic random variable. (Wikipedia).
Determining values of a variable at a particular percentile in a normal distribution
From playlist Unit 2: Normal Distributions
Using normal distribution to find the probability
👉 Learn how to find probability from a normal distribution curve. A set of data are said to be normally distributed if the set of data is symmetrical about the mean. The shape of a normal distribution curve is bell-shaped. The normal distribution curve is such that the mean is at the cente
From playlist Statistics
How to find the probability using a normal distribution curve
👉 Learn how to find probability from a normal distribution curve. A set of data are said to be normally distributed if the set of data is symmetrical about the mean. The shape of a normal distribution curve is bell-shaped. The normal distribution curve is such that the mean is at the cente
From playlist Statistics
How to find the probability using a normal distribution curve
👉 Learn how to find probability from a normal distribution curve. A set of data are said to be normally distributed if the set of data is symmetrical about the mean. The shape of a normal distribution curve is bell-shaped. The normal distribution curve is such that the mean is at the cente
From playlist Statistics
The Normal Distribution (1 of 3: Introductory definition)
More resources available at www.misterwootube.com
From playlist The Normal Distribution
What is a Unimodal Distribution?
Quick definition of a unimodal distribution and how it compares to a bimodal distribution and a multimodal distribution.
From playlist Probability Distributions
Statistics: Introduction to the Shape of a Distribution of a Variable
This video introduces some of the more common shapes of distributions http://mathispower4u.com
From playlist Statistics: Describing Data
Lect.3F: Log-Normal And Uniform Distributions
Lecture with Per B. Brockhoff. Chapters: 00:00 - The Log-Normal Distribution; 04:15 - Example 6; 07:00 - The Uniform Distribution; 08:00 - Example 7;
From playlist DTU: Introduction to Statistics | CosmoLearning.org
What is a Sampling Distribution?
Intro to sampling distributions. What is a sampling distribution? What is the mean of the sampling distribution of the mean? Check out my e-book, Sampling in Statistics, which covers everything you need to know to find samples with more than 20 different techniques: https://prof-essa.creat
From playlist Probability Distributions
Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 17-erm for probabilistic classif.
Professor Sanjay Lall Electrical Engineering To follow along with the course schedule and syllabus, visit: http://ee104.stanford.edu To view all online courses and programs offered by Stanford, visit: https://online.stanford.edu/
From playlist Stanford EE104: Introduction to Machine Learning Full Course
Harvesting Populations in Differential Equations (Differential Equations 38)
How Harvesting and Stocking effect the Logistic and Explosion/Extinction Differential Equations.
From playlist Differential Equations
Lecture 7/16 : Recurrent neural networks
Neural Networks for Machine Learning by Geoffrey Hinton [Coursera 2013] 7A Modeling sequences: A brief overview 7B Training RNNs with backpropagation 7C A toy example of training an RNN 7D Why it is difficult to train an RNN 7E Long term short term memory
From playlist Neural Networks for Machine Learning by Professor Geoffrey Hinton [Complete]
Differential equations are solved to the task of graphing the change in concentration of the prostate-specific antigen in prostate cancer patients. Note: Most equations are original to the writings of Ernest Rutherford.
From playlist Wolfram Technology Conference 2022
Stanford CS229: Machine Learning | Summer 2019 | Lecture 6 - Exponential Family & GLM
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3Eb7mIi Anand Avati Computer Science, PhD To follow along with the course schedule and syllabus, visit: http://cs229.stanford.edu/syllabus-summer2019.html
From playlist Stanford CS229: Machine Learning Course | Summer 2019 (Anand Avati)
Malwina Luczak: Near-criticality in mathematical models of epidemics
Recording during the meeting "Mathematical Modeling and Statistical Analysis of Infectious Disease Outbreaks" the February 20, 2020 at the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwi
From playlist Probability and Statistics
Geoffrey Hinton: "A Computational Principle that Explains Sex, the Brain, and Sparse Coding"
Graduate Summer School 2012: Deep Learning, Feature Learning "A Computational Principle that Explains Sex, the Brain, and Sparse Coding" Geoffrey Hinton, University of Toronto Institute for Pure and Applied Mathematics, UCLA July 11, 2012 For more information: https://www.ipam.ucla.edu/
From playlist GSS2012: Deep Learning, Feature Learning
Lecture 5 | Machine Learning (Stanford)
Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng lectures on generative learning algorithms and Gaussian discriminative analysis and their applications in machine learning. This course provides a broad introduction
From playlist Lecture Collection | Machine Learning
Geoffrey Hinton: "Using Backpropagation for Fine-Tuning a Generative Model..."
Graduate Summer School 2012: Deep Learning, Feature Learning "Part 2: Using Backpropagation for Fine-Tuning a Generative Model to be Better at Discrimination" Geoffrey Hinton, University of Toronto Institute for Pure and Applied Mathematics, UCLA July 9, 2012 For more information: https
From playlist GSS2012: Deep Learning, Feature Learning
Learning to find the probability using normal distribution
👉 Learn how to find probability from a normal distribution curve. A set of data are said to be normally distributed if the set of data is symmetrical about the mean. The shape of a normal distribution curve is bell-shaped. The normal distribution curve is such that the mean is at the cente
From playlist Statistics
Lecture 4 | Machine Learning (Stanford)
Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng lectures on Newton's method, exponential families, and generalized linear models and how they relate to machine learning. This course provides a broad introduction to
From playlist Lecture Collection | Machine Learning