(ML 4.1) Maximum Likelihood Estimation (MLE) (part 1)
Definition of maximum likelihood estimates (MLEs), and a discussion of pros/cons. A playlist of these Machine Learning videos is available here: http://www.youtube.com/my_playlists?p=D0F06AA0D2E8FFBA
From playlist Machine Learning
Learn to use summation notation for an arithmetic series to find the sum
👉 Learn how to find the partial sum of an arithmetic series. A series is the sum of the terms of a sequence. An arithmetic series is the sum of the terms of an arithmetic sequence. The formula for the sum of n terms of an arithmetic sequence is given by Sn = n/2 [2a + (n - 1)d], where a is
From playlist Series
Visualizing the Alternating Series Estimation Theorem
This video is a submission to 3Blue1Brown's Summer of Math Exposition competition. Learn more about it here: https://www.3blue1brown.com/blog/some1 3Blue1Brown's channel: https://www.youtube.com/channel/UCYO_jab_esuFRV4b17AJtAw This video hopefully helps the viewer visualize why the Alter
From playlist Summer of Math Exposition Youtube Videos
Finding the sum or an arithmetic series using summation notation
👉 Learn how to find the partial sum of an arithmetic series. A series is the sum of the terms of a sequence. An arithmetic series is the sum of the terms of an arithmetic sequence. The formula for the sum of n terms of an arithmetic sequence is given by Sn = n/2 [2a + (n - 1)d], where a is
From playlist Series
Evaluating the partial sum of a arithmetic series
👉 Learn how to find the partial sum of an arithmetic series. A series is the sum of the terms of a sequence. An arithmetic series is the sum of the terms of an arithmetic sequence. The formula for the sum of n terms of an arithmetic sequence is given by Sn = n/2 [2a + (n - 1)d], where a is
From playlist Series
Alternating Series Estimation Theorem
Thanks to all of you who support me on Patreon. You da real mvps! $1 per month helps!! :) https://www.patreon.com/patrickjmt !! Alternating Series Estimation Theorem -The basic idea along with a couple of examples are shown. For more free math videos, check out http://PatrickJMT.com
From playlist Sequence and Series Video Tutorial
Introduction to Estimation Theory
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. General notion of estimating a parameter and measures of estimation quality including bias, variance, and mean-squared error.
From playlist Estimation and Detection Theory
ETH Lecture 04. Project Management II: Quality Control (13/10/2011)
Course: Systems Dynamics and Complexity (Fall 2011) from ETH Zurich. Source: http://www.video.ethz.ch/lectures/d-mtec/2011/autumn/351-0541-00L.html
From playlist ETH Zürich: Systems Dynamics and Complexity (Fall 2011) | CosmoLearning Mathematics
Ex: Number of Terms Needed in Partial Sum to Estimate an Infinite Sum with a Given Error.
This video explains how many terms are needed in a partial sum of an alternating series to estimate the infinite with a given error. Site: http://mathispower4u.com
From playlist Infinite Series
On HOLD - Real Time Battery Pack Simulation Using Multicore Computers
Learn more on developing battery management systems: http://bit.ly/2P6Z6DA An accurate battery pack model is essential for hardware in-the-loop testing of Battery Management System (BMS). Get free resources on Battery Management systems: http://bit.ly/2P1PA4A Download a trial: http://bit
From playlist Power Electronics Control Design
Weinan E: "Machine learning based multi-scale modeling"
Machine Learning for Physics and the Physics of Learning 2019 Workshop II: Interpretable Learning in Physical Sciences "Machine learning based multi-scale modeling" Weinan E - Princeton University, Mathematics Abstract: We will discuss a general methodology for developing reliable and in
From playlist Machine Learning for Physics and the Physics of Learning 2019
DDPS | Machine Learning and Multi-scale Modeling
Description: Multi-scale modeling is an ambitious program that aims at unifying the different physical models at different scales for the practical purpose of developing accurate models and simulation protocols for properties of interest. Although the concept of multi-scale modeling is ver
From playlist Data-driven Physical Simulations (DDPS) Seminar Series
Free View Synthesis Gernot Riegler and Vladlen Koltun European Conference on Computer Vision (ECCV), 2020 Paper: http://vladlen.info/papers/FVS.pdf Code and data: https://github.com/intel-isl/FreeViewSynthesis We present a method for novel view synthesis from input images that are freely
From playlist AI Research
RubyConf 2016 - Opening Keynote by Yukihiro 'Matz' Matsumoto
RubyConf 2016 - Opening Keynote by Yukihiro 'Matz' Matsumoto
From playlist RubyConf 2016
Watch more videos on http://www.brightstorm.com/math/geometry SUBSCRIBE FOR All OUR VIDEOS! https://www.youtube.com/subscription_center?add_user=brightstorm2 VISIT BRIGHTSTORM.com FOR TONS OF VIDEO TUTORIALS AND OTHER FEATURES! http://www.brightstorm.com/ LET'S CONNECT! Facebook â–º https
From playlist Geometry
RailsConf 2017: Your App Server Config is Wrong by Nate Berkopec
RailsConf 2017: Your App Server Config is Wrong by Nate Berkopec As developers we spend hours optimizing our code, often overlooking a simpler, more efficient way to make quick gains in performance: application server configuration. Come learn about configuration failures that could be s
From playlist RailsConf 2017
Alternating Series | Estimating Remainers
Learning Objectives: 1) Estimate an Alternating Series by a formula that controls the remainder This video is part of a Calculus II course taught at the University of Cincinnati.
From playlist Older Calculus II (New Playlist For Spring 2019)
(ML 4.2) Maximum Likelihood Estimation (MLE) (part 2)
Definition of maximum likelihood estimates (MLEs), and a discussion of pros/cons. A playlist of these Machine Learning videos is available here: http://www.youtube.com/my_playlists?p=D0F06AA0D2E8FFBA
From playlist Machine Learning
Lec 4 | MIT 6.189 Multicore Programming Primer, IAP 2007
Lecture 4: Introduction to concurrent programming License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu Subtitles are provided through the generous assistance of Rohan Pai.
From playlist MIT 6.189 Multicore Programming Primer, January (IAP) 2007