11_3_1 The Gradient of a Multivariable Function
Using the partial derivatives of a multivariable function to construct its gradient vector.
From playlist Advanced Calculus / Multivariable Calculus
Definition of derivative in terms of a limit, (def 1)
Definition of derivative, calculus 1 homework solution. #calculus Check out my 100 derivatives: https://youtu.be/AegzQ_dip8k
From playlist Sect 2.7, Definition of Derivative
Ex : Determine The Value of a Derivative using the Limit Definition (Rational)
This video explains how to determine the value of a derivative at a given value of x using the limit definition of the derivative. The results are verified graphically http://mathispower4u.com
From playlist Introduction and Formal Definition of the Derivative
derivative of x^-2 with the definition of derivative
We use the definition of derivative to find the derivative of x^-2. For more calculus tutorials, please see my new "just calculus" channel: 👉https://www.youtube.com/justcalculus If you find my videos helpful, then consider supporting me on Patreon: 👉 https://www.patreon.com/blackpenred
From playlist Sect 2.7, Definition of Derivative
Multivariable Calculus | The gradient and directional derivatives.
We define the gradient of a function and show how it is helpful in finding the directional derivative. http://www.michael-penn.net http://www.randolphcollege.edu/mathematics/
From playlist Multivariable Calculus
Calculus 3.03d - Derivative Example 3
Another example of finding a derivative using the definition of a derivative.
From playlist Calculus Ch 3 - Derivatives
Test for Influential Observations
Regression Analysis by Dr. Soumen Maity,Department of Mathematics,IIT Kharagpur.For more details on NPTEL visit http://nptel.ac.in
From playlist IIT Kharagpur: Regression Analysis | CosmoLearning.org Mathematics
Garvesh Raskutti - Algorithmic and statistical perspectives of randomized sketching...
Garvesh Raskutti - Algorithmic and statistical perspectives of randomized sketching for ordinary least-squares In large-scale data settings, randomized 'sketching' has become an increasingly popular tool. In the numerical linear algebra literature, randomized sketching based on ei
From playlist Schlumberger workshop - Computational and statistical trade-offs in learning
(New Version Available) Inverse Functions
New Version: https://youtu.be/q6y0ToEhT1E Define an inverse function. Determine if a function as an inverse function. Determine inverse functions. http://mathispower4u.wordpress.com/
From playlist Exponential and Logarithmic Expressions and Equations
NIPS 2011 Sparse Representation & Low-rank Approximation Workshop: Fast Approximation...
Sparse Representation and Low-rank Approximation Workshop at NIPS 2011 Invited Talk: Fast Approximation of Matrix Coherence and Statistical Leverage by Michael Mahoney, Stanford University Michael Mahoney is in the math department at Stanford University. Much of his current research
From playlist NIPS 2011 Sparse Representation & Low-rank Approx Workshop
Lecturer: Dr. Erin M. Buchanan Spring 2021 https://www.patreon.com/statisticsofdoom This video covers the basics of linear regression including assumptions, hypothesis testing, how to understand overall models and coefficients, how to examine for outliers, and how to run categorical va
From playlist Graduate Statistics Flipped
Nonlinear dimensionality reduction for faster kernel methods in machine learning - Christopher Musco
Computer Science/Discrete Mathematics Seminar I Topic: Nonlinear dimensionality reduction for faster kernel methods in machine learning. Speaker: Christopher Musco Affiliation: Massachusetts Institute of Technology Date: Febuary 12, 2018 For more videos, please visit http://video.ias.edu
From playlist Mathematics
Inverse Trigonometric Derivatives f(x) = arctan(lnx)
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Inverse Trigonometric Derivatives f(x) = arctan(lnx)
From playlist Calculus
SPSS - Hierarchical Multiple Linear Regression
Lecturer: Dr. Erin M. Buchanan Missouri State University Spring 2015 This video covers hierarchical linear regression in SPSS, along with data screening procedures from Tabachnick and Fidell (2014). Lecture materials and assignments available at statisticsofdoom.com. https://statistics
From playlist Advanced Statistics Videos
O'Reilly Webcast Computational Thinking Just Enough Math
The webcast introduces advanced math for business people — "just enough" to take advantage of open source frameworks — including graph theory, abstract algebra, optimization, bayesian statistics, and more advanced areas of linear algebra. These are needed for supply chain optimization, pri
From playlist O'Reilly Webcasts 3
R - Mediation Analyses with the multilevel package
Lecturer: Dr. Erin M. Buchanan Missouri State University Spring 2018 This video replaces a previous live in-class video. You will learn how to do mediation analyses in regression. First, we start with power in G*Power, work through data screening, and then analyze the stages of mediation
From playlist Learn and Use G*Power
SPSS - Mediation Analysis with PROCESS
Lecturer: Dr. Erin M. Buchanan Missouri State University Spring 2015 Mediation analysis video covering model 4 in the process plug in (Hayes, 2013). Lecture materials and assignments available at statisticsofdoom.com. https://statisticsofdoom.com/page/advanced-statistics/
From playlist PSY 527/627 (SPSS) Advanced Statistics with Dr. B
11_7_1 Potential Function of a Vector Field Part 1
The gradient of a function is a vector. n-Dimensional space can be filled up with countless vectors as values as inserted into a gradient function. This is then referred to as a vector field. Some vector fields have potential functions. In this video we start to look at how to calculat
From playlist Advanced Calculus / Multivariable Calculus
Stanford ENGR108: Introduction to Applied Linear Algebra | 2020 | Lecture 47-VMLS portfolio optim
Professor Stephen Boyd Samsung Professor in the School of Engineering Director of the Information Systems Laboratory To follow along with the course schedule and syllabus, visit: https://web.stanford.edu/class/engr108/ To view all online courses and programs offered by Stanford, visit:
From playlist Stanford ENGR108: Introduction to Applied Linear Algebra —Vectors, Matrices, and Least Squares
Example on gradient identities for functions of two variables.
From playlist Engineering Mathematics