What Are Error Intervals? GCSE Maths Revision
What are error Intervals and how do we find them - that's the mission in this episode of GCSE Maths minis! Error Intervals appear on both foundation and higher tier GCSE maths and IGCSE maths exam papers, so this is excellent revision for everyone! DOWNLOAD THE QUESTIONS HERE: https://d
From playlist Error Intervals & Bounds GCSE Maths Revision
Brief overview of the standard error. What it represents and how you would find it with a formula.
From playlist Basic Statistics (Descriptive Statistics)
From playlist a. Numbers and Measurement
How to calculate margin of error and standard deviation
In this tutorial I show the relationship standard deviation and margin of error. I calculate margin of error and confidence intervals with different standard deviations. Playlist on Confidence Intervals http://www.youtube.com/course?list=EC36B51DB57E3A3E8E Like us on: http://www.facebook
From playlist Confidence Intervals
How to Find Standard Error in Excel 2013
Visit us at http://www.statisticshowto.com for more Excel statistics videos and tips.
From playlist Excel for Statistics
Brief intro the the linear regression formula and errors.
From playlist Regression Analysis
Standard Error of the Estimate used in Regression Analysis (Mean Square Error)
An example of how to calculate the standard error of the estimate (Mean Square Error) used in simple linear regression analysis. This typically taught in statistics. Like us on: http://www.facebook.com/PartyMoreStud... Link to Playlist on Regression Analysis http://www.youtube.com/cour
From playlist Linear Regression.
Linear classifiers (2): Learning parameters
Perceptron algorithm, logistic regression, and surrogate loss functions
From playlist cs273a
Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 8 - non quadratic losses
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
Linear regression (3): Normal equations
Closed form solution for mean squared error; normal equations; robustness and other losses
From playlist cs273a
Coding Up a Linear Regression Algorithm From Scratch
Whether we learn Data Science through online courses, tutorials, or jump straight into a hands-on project-based approach, few of us take out the time to try and learn how some of our favorite libraries are built. All we know is that we can import the scikit-learn library, instantiate a Lin
From playlist Brief Introduction to Data Science
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
Loss Functions for Causal Inference
Professor Stefan Wager distills best practices for causal inference into loss functions.
From playlist Machine Learning & Causal Inference: A Short Course
Deep Learning Lecture 3.4 - Backpropagation
Deep Learning Lecture - Backpropagation Algorithm for neural network training.
From playlist Deep Learning Lecture
Frank Noé: "Intro to Machine Learning (Part 1/2)"
Watch part 2/2 here: https://youtu.be/7TZnGQrNF6g Machine Learning for Physics and the Physics of Learning Tutorials 2019 "Intro to Machine Learning (Part 1/2)" Frank Noé, Freie Universität Berlin Institute for Pure and Applied Mathematics, UCLA September 5, 2019 For more information:
From playlist Machine Learning for Physics and the Physics of Learning 2019
Stanford EE104: Introduction to Machine Learning | 2020 | Lecture 6 - empirical risk minimization
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/ 0:00 Introduction 0:26 Parametrized predictors 3:09 Tra
From playlist Stanford EE104: Introduction to Machine Learning Full Course
Uncertainty and Propagation of Errors
A discussion of how to report experimental uncertainty, and how to calculate propagation of errors. Based on the nice video by paulcolor: https://youtu.be/V0ZRvvHfF0E, with some personal edits.
From playlist Experimental Physics