(ML 11.4) Choosing a decision rule - Bayesian and frequentist
Choosing a decision rule, from Bayesian and frequentist perspectives. To make the problem well-defined from the frequentist perspective, some additional guiding principle is introduced such as unbiasedness, minimax, or invariance.
From playlist Machine Learning
Transformer (Attention is all you need)
understanding Transformer with its key concepts (attention, multi head attention, positional encoding, residual connection label smoothing) with example. all machine learning youtube videos from me, https://www.youtube.com/playlist?list=PLVNY1HnUlO26x597OgAN8TCgGTiE-38D6
From playlist Machine Learning
Management Tutorial - Employee recognition tips
Learn ways to recognize employees regularly so they hear that what they do matters, and feel that they matter. Explore more Leadership and Management courses and advance your skills on LinkedIn Learning: https://www.linkedin.com/learning/topics/leadership-and-management?trk=sme-youtube_M14
From playlist Leadership and Management
In this video, you’ll learn strategies for making decisions large and small. Visit https://edu.gcfglobal.org/en/problem-solving-and-decision-making/ for our text-based tutorial. We hope you enjoy!
From playlist Making Decisions
Pattern Matching - Correctness
Learn how to use pattern matching to assist you in your determination of correctness. This video contains two examples, one with feedback and one without. https://teacher.desmos.com/activitybuilder/custom/6066725595e2513dc3958333
From playlist Pattern Matching with Computation Layer
PSY 523 Word Recognition Part 1
Lecturer: Dr. Erin M. Buchanan Missouri State University Summer/Fall 2016 PSY 523 Psychology and Language lectures covering material from Harley's The Psychology of Language: From Data to Theory. Lecture materials and assignments available at statisticsofdoom.com. https://statisticsofdo
From playlist PSY 523 Psychology and Language
PSY 523 Word Recognition Part 2
Lecturer: Dr. Erin M. Buchanan Missouri State University Summer/Fall 2016 PSY 523 Psychology and Language lectures covering material from Harley's The Psychology of Language: From Data to Theory. Lecture materials and assignments available at statisticsofdoom.com. https://statisticsofdo
From playlist PSY 523 Psychology and Language
PSY 523 Word Recognition Part 3
Lecturer: Dr. Erin M. Buchanan Missouri State University Summer/Fall 2016 PSY 523 Psychology and Language lectures covering material from Harley's The Psychology of Language: From Data to Theory. Lecture materials and assignments available at statisticsofdoom.com. https://statisticsofdoo
From playlist PSY 523 Psychology and Language
Fairness in commercial face recognition algorithms
Session 3 – Dr Santhosh Narayanan, The Alan Turing Institute
From playlist Trustworthy Digital Identity – Workshop, December 2022
Stanford Digital Transformation Certificate Program
Learn more: https://stanford.io/3LF0MxG It is not a question of "if" your company should take on a digital transformation, but "how." The Digital Transformation Program provides a comprehensive framework for implementing digital transformation throughout your company. It brings together p
From playlist Leadership & Management
Recorded: Spring 2014 Lecturer: Dr. Erin M. Buchanan Materials: created for Memory and Cognition (PSY 422) using Smith and Kosslyn (2006) Lecture materials and assignments available at statisticsofdoom.com. https://statisticsofdoom.com/page/other-courses/
From playlist PSY 422 Memory and Cognition with Dr. B
PSY 523 Word Recognition Part 4
Lecturer: Dr. Erin M. Buchanan Missouri State University Summer/Fall 2016 PSY 523 Psychology and Language lectures covering material from Harley's The Psychology of Language: From Data to Theory. Lecture materials and assignments available at statisticsofdoom.com. https://statisticsofdo
From playlist PSY 523 Psychology and Language
Towards Robust Deep Learning (Remote talk) by Stephan Zheng
DISCUSSION MEETING THE THEORETICAL BASIS OF MACHINE LEARNING (ML) ORGANIZERS: Chiranjib Bhattacharya, Sunita Sarawagi, Ravi Sundaram and SVN Vishwanathan DATE : 27 December 2018 to 29 December 2018 VENUE : Ramanujan Lecture Hall, ICTS, Bangalore ML (Machine Learning) has enjoyed tr
From playlist The Theoretical Basis of Machine Learning 2018 (ML)
4.2 - Introduction to Machine Learning
Information Service Engineering 2021 Prof. Dr. Harald Sack Karlsruhe Institute of Technology Summer semester 2021 Lecture 10: Basic Machine Learning - 1 4.2 Introduction to Machine Learning - How do we learn? - Definition of machine learning - supervised and unsupervised learning - regre
From playlist ISE2021 - Lecture 10 - 23.06.2021
When you get a bacterial infection, the immune response needs to be very rapid. But it can take hours to sense a threat, and generating effector proteins in response takes time. Luckily, we all have large protein complexes called inflammasomes that can also initiate inflammation. What are
From playlist Immunology
Alan Alda talks to legal expert Nita Farahany and neuroscientist Anthony Wagner, who say that fMRI studies show that we cannot rely on our memories to be accurate. But technology to prove this is not yet ready for the courtroom.
From playlist General Science
Basics of Machine Learning: Geordie Williamson
Machine Learning for the Working Mathematician: Week One 25 February 2022 Geordie Williamson, Basics of Machine Learning: classic problems in machine learning, kernel methods, deep neural networks, supervised learning, and basic examples. Seminar series homepage (includes Zoom link): htt
From playlist Machine Learning for the Working Mathematician
Inclusion by design: Creating digital identity solutions that work for all
The need for improved digital identity systems and infrastructure has been a pressing requirement for many years, as more businesses have moved their operations online. The pandemic presents us with a unique opportunity to enable economic and societal value creation as digital identity sys
From playlist Turing trustworthy digital identity conference