Determining if two events are mutually exclusive or not
👉 Learn how to find the probability of mutually exclusive events. Two events are said to be mutually exclusive when the two events cannot occur at the same time. For instance, when you throw a coin the event that a head appears and the event that a tail appears are mutually exclusive becau
From playlist Probability of Mutually Exclusive Events
How to find the probability between two mutually exclusive events
👉 Learn how to find the probability of mutually exclusive events. Two events are said to be mutually exclusive when the two events cannot occur at the same time. For instance, when you throw a coin the event that a head appears and the event that a tail appears are mutually exclusive becau
From playlist Probability of Mutually Exclusive Events
How to find the probability of mutually exclusive event with a die
👉 Learn how to find the probability of mutually exclusive events. Two events are said to be mutually exclusive when the two events cannot occur at the same time. For instance, when you throw a coin the event that a head appears and the event that a tail appears are mutually exclusive becau
From playlist Probability of Mutually Exclusive Events
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
R - Association Measures: Collocations, PMI, and Co-occurrence
Lecturer: Dr. Erin M. Buchanan Summer 2019 https://www.patreon.com/statisticsofdoom This video is part of my human language modeling class. This video explores the relationship between words (or any data you can convert to numbers!) using association through point wise mutual informatio
From playlist Human Language (ANLY 540)
Dimensionality Reduction | Stanford CS224U Natural Language Understanding | Spring 2021
For more information about Stanford's Artificial Intelligence professional and graduate programs visit: https://stanford.io/ai To learn more about this course visit: https://online.stanford.edu/courses/cs224u-natural-language-understanding To follow along with the course schedule and sy
From playlist Stanford CS224U: Natural Language Understanding | Spring 2021
Ex: Find First and Second Order Partial Derivatives
This video explains how to find first and second order partial derivatives. They are also evaluated at a point and the meaning of the value is illustrated graphically. Site: http://mathispower4u.com
From playlist Partial Derivatives of functions of Two or More Variables
Lecture 2 – Word Vectors 1 | Stanford CS224U: Natural Language Understanding | Spring 2019
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai Professor Christopher Potts & Consulting Assistant Professor Bill MacCartney, Stanford University http://onlinehub.stanford.edu/ Professor Christopher Potts Pr
From playlist Stanford CS224U: Natural Language Understanding | Spring 2019
Lecture 3 – Word Vectors 2 | Stanford CS224U: Natural Language Understanding | Spring 2019
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai Professor Christopher Potts & Consulting Assistant Professor Bill MacCartney, Stanford University http://onlinehub.stanford.edu/ Professor Christopher Potts Pr
From playlist Stanford CS224U: Natural Language Understanding | Spring 2019
Mutually Exclusive or Disjoint Events in Probability
Understanding and identifying mutual events, known as disjoint events.
From playlist Unit 5 Probability A: Basic Probability
Linear Second Order Homogeneous Differential Equations - (two distict real roots)
This is a lesson on linear second order homogeneous differential equations with constant coefficients when the characteristic equations has two real distinct roots. Site: http://mathispower4u.com
From playlist Linear Second Order Homogeneous Differential Equations (Constant Coefficients)
2nd Order Differential Equation The Characteristic Equation
We demonstrate how to solve a 2nd order, linear, homogeneous differential equation with constant coefficients with "guess and check," and the characteristic equation.
From playlist Mathematical Physics I Uploads
Is Automated Topic Model Evaluation Broken?: The Incoherence of Coherence [Paper Read Out Loud]
http://umiacs.umd.edu/~jbg//docs/2021_neurips_incoherence.pdf
From playlist Papers Read Aloud
Lecturer: Dr. Erin M. Buchanan Summer 2020 https://www.patreon.com/statisticsofdoom This video is part of my human language modeling class - this video set covers the updated version with both R and Python. This section covers similarity - cosine, point wise mutual information, and more
From playlist Human Language (ANLY 540)
Given y1 and y2 Solutions to a 2nd Order DE, Find the Wronskian and Part Solution (e^(-t)cos(2t))
This video explains how to determine the Wronskian and then the general solutions to a linear second order homogeneous differential equation.
From playlist Second Order Differential Equations
Cryptanalysis of Classical Ciphers
Cryptography and Network Security by Prof. D. Mukhopadhyay, Department of Computer Science and Engineering, IIT Kharagpur. For more details on NPTEL visit http://nptel.iitm.ac.in
From playlist Computer - Cryptography and Network Security
11. RNA Secondary Structure; Biological Functions and Predictions
MIT 7.91J Foundations of Computational and Systems Biology, Spring 2014 View the complete course: http://ocw.mit.edu/7-91JS14 Instructor: Christopher Burge Lecture 11 is about RNA secondary structure. Â Prof. Christopher Burge begins with an introduction and biological examples of RNA stru
From playlist MIT 7.91J Foundations of Computational and Systems Biology
Negativity and semantic change - Will Hamilton, Stanford University
It is often argued that natural language is biased towards negative differentiation, meaning that there is more lexical diversity in negative affectual language, compared to positive language. However, we lack an understanding of the diachronic linguistic mechanisms associated with negativ
From playlist Turing Seminars
Anna Vershynina: "Quasi-relative entropy: the closest separable state & reversed Pinsker inequality"
Entropy Inequalities, Quantum Information and Quantum Physics 2021 "Quasi-relative entropy: the closest separable state and the reversed Pinsker inequality" Anna Vershynina - University of Houston Abstract: It is well known that for pure states the relative entropy of entanglement is equ
From playlist Entropy Inequalities, Quantum Information and Quantum Physics 2021