Generalized linear models | Actuarial science | Regression models
In statistics, the class of vector generalized linear models (VGLMs) was proposed to enlarge the scope of models catered for by generalized linear models (GLMs).In particular, VGLMs allow for response variables outside the classical exponential familyand for more than one parameter. Each parameter (not necessarily a mean) can be transformed by a link function.The VGLM framework is also large enough to naturally accommodate multiple responses; these areseveral independent responses each coming from a particular statistical distribution withpossibly different parameter values. Vector generalized linear models are described in detail in Yee (2015).The central algorithm adopted is the iteratively reweighted least squares method,for maximum likelihood estimation of usually all the model parameters. In particular, Fisher scoring is implemented by such, which, for most models,uses the first and expected second derivatives of the log-likelihood function. (Wikipedia).
Linear Algebra for Computer Scientists. 1. Introducing Vectors
This computer science video is one of a series on linear algebra for computer scientists. This video introduces the concept of a vector. A vector is essentially a list of numbers that can be represented with an array or a function. Vectors are used for data analysis in a wide range of f
From playlist Linear Algebra for Computer Scientists
Visualization of tensors - part 1
This video visualizes tensors. It shows some introduction to tensor theory and demonstrates it with the Cauchy stress tensor. Future parts of this series will show more theory and more examples. It talks about the term 'tensor' as used in physics and math. In the field of AI the term 'te
From playlist Animated Physics Simulations
Vector and matrix forms for systems of linear equations | Linear Algebra MATH1141 | N J Wildberger
A system of linear equations may also be viewed in vector form, as an attempt to write one vector as a linear combination of other vectors. Or it more alternatively be viewed in matrix form. We discuss the matrix of coefficients, the vector of variables and the vector of constants. Puttin
From playlist Higher Linear Algebra
This shows an small game that illustrates the concept of a vector. The clip is from the book "Immersive Linear Algebra" at http://www.immersivemath.com
From playlist Chapter 2 - Vectors
Vector Calculus 1: What Is a Vector?
https://bit.ly/PavelPatreon https://lem.ma/LA - Linear Algebra on Lemma http://bit.ly/ITCYTNew - Dr. Grinfeld's Tensor Calculus textbook https://lem.ma/prep - Complete SAT Math Prep
From playlist Vector Calculus
Generalized Coordinates & Equations of Motion | Classical Mechanics
When we consider a system of objects in classical mechanics, we can describe those objects with many different coordinate systems. Sometimes cartesian coordinates are most useful, some other times we might choose cylindrical coordinates. But there is also a way to view this system independ
From playlist Classical Mechanics
Ex: Find a Unit Vector in the Direction of a Given Vector in 3D
This example explains how to find a unit vector in the direction of a given vector in space. Site: http://mathispower4u.com
From playlist Vectors in Space (3D)
Mod-01 Lec-01 Introduction and Overview
Advanced Numerical Analysis by Prof. Sachin C. Patwardhan,Department of Chemical Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.ac.in
From playlist IIT Bombay: Advanced Numerical Analysis | CosmoLearning.org
Stanford CS229: Machine Learning | Summer 2019 | Lecture 23 - Course Recap and Wrap Up
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3B6WitS 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)
CSE 519 -- Lecture 19, Fall 2020
From playlist CSE 519 -- Fall 2020
Stanford CS229: Machine Learning | Summer 2019 | Lecture 10 - Deep learning - I
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3E5G0U6 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)
Deep Generative models and Inverse Problems - Alexandros Dimakis
Seminar on Theoretical Machine Learning Topic:Deep Generative models and Inverse Problems Speaker: Alexandros Dimakis Affiliation: University of Texas at Austin Date: April 23, 2020 For more video please visit http://video.ias.edu
From playlist Mathematics
How to compute the length and direction of a vector. Free ebook Free ebook https://bookboon.com/en/introduction-to-vectors-ebook (updated link) Test your understanding via a short quiz http://goo.gl/forms/0hPXc99Ql9
From playlist Introduction to Vectors
Stanford CS229: Machine Learning | Summer 2019 | Lecture 8 - Kernel Methods & Support Vector Machine
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3DYVYzo 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)
Efficient Zero Knowledge Proofs - A Modular Approach (Lecture 2) by Yuval Ishai
DISCUSSION MEETING : FOUNDATIONAL ASPECTS OF BLOCKCHAIN TECHNOLOGY ORGANIZERS : Pandu Rangan Chandrasekaran DATE : 15 to 17 January 2020 VENUE : Madhava Lecture Hall, ICTS, Bangalore Blockchain technology is among one of the most influential disruptive technologies of the current decade.
From playlist Foundational Aspects of Blockchain Technology 2020
Mod-01 Lec-24 Model Parameter Estimation using Gauss-Newton Method
Advanced Numerical Analysis by Prof. Sachin C. Patwardhan,Department of Chemical Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.ac.in
From playlist IIT Bombay: Advanced Numerical Analysis | CosmoLearning.org
Multivariable Calculus | The notion of a vector and its length.
We define the notion of a vector as it relates to multivariable calculus and define its length. http://www.michael-penn.net http://www.randolphcollege.edu/mathematics/
From playlist Vectors for Multivariable Calculus
Parsimonious Representations in data science - Dr Armin Eftekhari, University of Edinburgh
Every minute, humankind produces about 2000 Terabytes of data and learning from this data has the potential to improve many aspects of our lives. Doing so requires exploiting the geometric structure hidden within the data. Our overview of models in data and computational sciences starts wi
From playlist Data science classes