Probabilistic model 5: summary of assumptions
[http://bit.ly/BM-25] The summary of 7 assumptions made in the probabilistic model of IR, and why really need to make them. What assumptions can we relax?
From playlist Probabilistic Model of IR
Calculating Binomial Probabilities with SPSS
This demonstration shows you how to find binomial probabilities using the statistical software package SPSS. This demonstration corresponds to the Introduction to Statistics, Think & Do textbook, by Scott Stevens (http://www.StevensStats.com).
From playlist SPSS Demonstrations
Three Ways to Generate Probabilities
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Three Ways to Generate Probabilities
From playlist Statistics
Digging into Data: Probability Review
An overview of the course and data science. To be viewed before the first class on February 3, 2014.
From playlist Digging into Data
Probabilistic model 3: parameter estimation
[http://bit.ly/BM-25] How do we estimate the parameters for the probabilistic model of IR? When we have examples of relevant and non-relevant documents (relevance feedback) the estimation is very straightforward: we use maximum-likelihood estimates for Bernoulli random variables (relative
From playlist Probabilistic Model of IR
Probabiilty spaces, events and conditional probabilities | Probability and Statistics
We now introduce some more formal structures to talk about probabillities: first the idea of a sample space S--the possible outcomes of an experiment, and then the idea of a probability measure P on such a sample space. Together these two (S,P) make what we call a probability space. An e
From playlist Probability and Statistics: an introduction
Probabilistic logic programming and its applications - Luc De Raedt, Leuven
Probabilistic programs combine the power of programming languages with that of probabilistic graphical models. There has been a lot of progress in this paradigm over the past twenty years. This talk will introduce probabilistic logic programming languages, which are based on Sato's distrib
From playlist Logic and learning workshop
Alvaro Lozano-Robledo, The distribution of ranks of elliptic curves and the minimalist conjecture
VaNTAGe seminar, on Sep 29, 2020 License: CC-BY-NC-SA. An updated version of the slides that corrects a few minor issues can be found at https://math.mit.edu/~drew/vantage/LozanoRobledoSlides.pdf
From playlist Math Talks
Bayesian Networks 2 - Definition | Stanford CS221: AI (Autumn 2021)
For more information about Stanford's Artificial Intelligence professional and graduate programs visit: https://stanford.io/ai Associate Professor Percy Liang Associate Professor of Computer Science and Statistics (courtesy) https://profiles.stanford.edu/percy-liang Assistant Professor
From playlist Stanford CS221: Artificial Intelligence: Principles and Techniques | Autumn 2021
Deep Learning Lecture 10.1 - Probabilistic Models
Introduction to Probabilistic Models
From playlist Deep Learning Lecture
Fellow Short Talks: Dr Charles Sutton, Edinburgh University
Charles Sutton is a Reader (equivalent to Associate Professor: http://bit.ly/1W9UhqT) in Machine Learning at the University of Edinburgh. He has over 50 publications in a broad range of applications of probabilistic machine learning. His work in machine learning for software engineering ha
From playlist Short Talks
Bayesian Networks 3 - Probabilistic Programming | Stanford CS221: AI (Autumn 2021)
For more information about Stanford's Artificial Intelligence professional and graduate programs visit: https://stanford.io/ai Associate Professor Percy Liang Associate Professor of Computer Science and Statistics (courtesy) https://profiles.stanford.edu/percy-liang Assistant Professor
From playlist Stanford CS221: Artificial Intelligence: Principles and Techniques | Autumn 2021
22C3: Digital Identity and the Ghost in the Machine
Speaker: Max Kilger "Once I Was Lost But Now I've Been Found" The demarcation line that used to separate your digital identity from your real world physical identity is rapidly disappearing. More seriously, it is permanently changing the way in which the world sees you and you see yourse
From playlist 22C3: Private Investigations
An AP Statistics lecture introducing probabilities, randomness, Law of Large Numbers, Probability Model, Tree Diagram, 5 Rules of Probability,etc. Find free review test, useful notes and more at http://www.mathplane.com If you'd like to make a donation to support my efforts look for the "T
From playlist AP Statistics
Professor Dan Olteanu - University of Oxford
Dan Olteanu is Professor of Computer Science at Oxford and Computer Scientist at RelationalAI. He also consulted for LogicBlox and taught at the universities of California Berkeley, Munich, Saarland, and Heidelberg. He received his PhD in Computer Science from University of Munich in 2005.
From playlist Short Talks
An AP Statistics lecture introducing probabilities, randomness, Law of Large Numbers, Probability Model, Tree Diagram, 5 Rules of Probability,etc. Find free review test, useful notes and more at http://www.mathplane.com If you'd like to make a donation to support my efforts look for the "T
From playlist AP Statistics
Nexus trimester - Yitong Yin (Nanjing University)
Rectangle inequalities for data structure lower bounds Yitong Yin (Nanjing University) February 23, 2016 Abstract: The richness lemma is a classic rectangle-based technique for asymmetric communication complexity and cell-probe lower bounds. The technique was enhanced by the Patrascu-Thoru
From playlist Nexus Trimester - 2016 - Fundamental Inequalities and Lower Bounds Theme
Calculating Cumulative Binomial Probabilities with SPSS
This demonstration shows you how to find cumulative binomial probabilities using SPSS. This demonstration corresponds to Introduction to Statistics, Think & Do textbook, by Scott Stevens (http://www.StevensStats.com).
From playlist SPSS Demonstrations
The Covariance Matrix : Data Science Basics
What is the covariance matrix and how is it computed? --- Like, Subscribe, and Hit that Bell to get all the latest videos from ritvikmath ~ --- Check out my Medium: https://medium.com/@ritvikmathematics My Patreon: https://www.patreon.com/user?u=49277905
From playlist Data Science Basics
Clojure Conj 2012 - Clojure Data Science
Clojure Data Science by: Edmund Jackson Data science / big data exists at the overlap of traditional analytics and large scale computation. As such, neither the traditional tools of analytics (R, Mathematica, Matlab) nor mainstreams languages (Java, C++, C#) supply its requirements well a
From playlist Clojure Conf 2012