Error bounds for Taylor approximations -- Calculus II
This lecture is on Calculus II. It follows Part II of the book Calculus Illustrated by Peter Saveliev. The text of the book can be found at http://calculus123.com.
From playlist Calculus II
Polynomial approximations -- Calculus II
This lecture is on Calculus II. It follows Part II of the book Calculus Illustrated by Peter Saveliev. The text of the book can be found at http://calculus123.com.
From playlist Calculus II
B01 An introduction to numerical methods
Most differential equations cannot be solved by the analytical techniques that we have learned up until now. I these cases, we can approximate a solution by a set of points, by using a variety of numerical methods. The first of these is Euler's method.
From playlist A Second Course in Differential Equations
The first method for solving second order linear ODE's uses reduction in order. In this method the second derivative is reduced to a first derivative in the dependent variable, which can usually be solved by separation of variables, or by introduction an integrating factor.
From playlist Differential Equations
Convergence of Newton's Method | Lecture 17 | Numerical Methods for Engineers
Calculation of the order of convergence of Newton's method. Join me on Coursera: https://www.coursera.org/learn/numerical-methods-engineers Lecture notes at http://www.math.ust.hk/~machas/numerical-methods-for-engineers.pdf Subscribe to my channel: http://www.youtube.com/user/jchasnov?s
From playlist Numerical Methods for Engineers
C34 Expanding this method to higher order linear differential equations
I this video I expand the method of the variation of parameters to higher-order (higher than two), linear ODE's.
From playlist Differential Equations
Reduction of Order - Linear Second Order Homogeneous Differential Equations Part 2
This video explains how to apply the method of reduction of order to solve a linear second order homogeneous differential equations. Site: http://mathispower4u
From playlist Second Order Differential Equations: Reduction of Order
Table of Contents: 00:50 - Lecture structure Two Proportions 01:11 - Checking assumptions 02:50 - Computing the standard error by hand 03:59 - Example: Computing the standard error for a confidence interval 06:22 - Example: Computing the standard error for a hypothesis test 08
From playlist STAT 200 Video Lectures
2020.05.28 Andrew Stuart - Supervised Learning between Function Spaces
Consider separable Banach spaces X and Y, and equip X with a probability measure m. Let F: X \to Y be an unknown operator. Given data pairs {x_j,F(x_j)} with {x_j} drawn i.i.d. from m, the goal of supervised learning is to approximate F. The proposed approach is motivated by the recent su
From playlist One World Probability Seminar
Mod-01 Lec-36 Solving Nonlinear Algebraic Equations: Wegstein Method and Variants of Newton's 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
DDPS | A mathematical understanding of modern Machine Learning: theory, algorithms and applications
In this talk from July 15, 2021, Brown University assistant professor Yeonjong Shin discusses the development of robust and reliable machine learning algorithms based on insights gained from the mathematical analysis. Description: Modern machine learning (ML) has achieved unprecedented em
From playlist Data-driven Physical Simulations (DDPS) Seminar Series
Eric Goubault, École Polytechnique
April 5, Eric Goubault, École Polytechnique Reachability and invariance for the verification of control systems, some directions
From playlist Spring 2022 Online Kolchin seminar in Differential Algebra
Calculus 1 Newtons Method b3p1
Calculus 1 Newtons Method b3p1 Gotomath.com
From playlist Calculus 1 GoToMath.com
From playlist STAT 200 Video Lectures
Anh-Huy Phan: "Chain Tensor Network: Instability and how to deal with it"
Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021 Workshop III: Mathematical Foundations and Algorithms for Tensor Computations "Chain Tensor Network: Instability and how to deal with it" Anh-Huy Phan - Skolkovo Institute of Science and Technology Abstract:
From playlist Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021
Alexandre Tkatchenko: "Towards a Unified Machine Learning Model of Molecular Chemical Space"
Machine Learning for Physics and the Physics of Learning 2019 Workshop I: From Passive to Active: Generative and Reinforcement Learning with Physics "Towards a Unified Machine Learning Model of Molecular Chemical Space" Alexandre Tkatchenko, University of Luxembourg Institute for Pure an
From playlist Machine Learning for Physics and the Physics of Learning 2019
Calculate a Confidence Interval for a Population Proportion (Plus Four Method)
This lesson explains how to calculator a confidence interval for a population proportion using the Plus Four Method.
From playlist Confidence Intervals
Ex: Newton's Method to Approximate Zeros -- 2 Iterations
This video provides an example of how to approximate zeros or roots of a polynomial equation using Newton's Method. Two iterations are provided. Site: http://mathispower4u.com
From playlist Newton’s Method and L’Hopital’s Rule