PPT-CS239-Lecture 16 Distributed Machine Learning
Author : lois-ondreau | Published Date : 2018-10-05
Madan Musuvathi Visiting Professor UCLA Principal Researcher Microsoft Research Course Project Writeups due June 1 st Project presentations 12 presentations 10
Presentation Embed Code
Download Presentation
Download Presentation The PPT/PDF document "CS239-Lecture 16 Distributed Machine Lea..." is the property of its rightful owner. Permission is granted to download and print the materials on this website for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.
CS239-Lecture 16 Distributed Machine Learning: Transcript
Madan Musuvathi Visiting Professor UCLA Principal Researcher Microsoft Research Course Project Writeups due June 1 st Project presentations 12 presentations 10 mins each 15 min slack. Andersen Jun Woo Park Alexander J Smola Amr Ahmed Vanja Josifovski James Long Eugene J Shekita BorYiing Su Carnegie Mellon University Baidu Google muli dga junwoop cscmuedu alexsmolaorg amra vanjaj jamlong shekita boryiingsu googlecom Abstract Easy to understand Easy to code by hand Often used to represent inputs to a net Easy to learn This is what mixture models do Each cluster corresponds to one neuron Easy to associate with other representations or responses But localist models are ver Clustering and pattern recognition. W. ikipedia entry on machine learning. 7.1 Decision tree learning. 7.2 Association rule learning. 7.3 Artificial neural networks. 7.4 Genetic programming. 7.5 Inductive logic programming. . Machine Learning. ETHEM . ALPAYDIN. © The MIT Press, . 2010. alpaydin@boun.edu.tr. http://www.cmpe.boun.edu.tr/~. ethem/i2ml2e. Lecture Slides for. CHAPTER 2:. . Supervised Learning. Learning a Class from Examples. Lecture . 4. Multilayer . Perceptrons. G53MLE | Machine Learning | Dr Guoping Qiu. 1. Limitations of Single Layer Perceptron. Only express linear decision surfaces. G53MLE | Machine Learning | Dr Guoping Qiu. R/Finance. 20 May 2016. Rishi K Narang, Founding Principal, T2AM. What the hell are we talking about?. What the hell is machine learning?. How the hell does it relate to investing?. Why the hell am I mad at it?. David Kauchak. CS 451 – Fall 2013. Why are you here?. What is Machine Learning?. Why are you taking this course?. What topics would you like to see covered?. Machine Learning is…. Machine learning, a branch of artificial intelligence, concerns the construction and study of systems that can learn from data.. COS 518: Advanced Computer Systems. Lecture . 13. Daniel Suo. Outline. 2. What is machine learning?. Why is machine learning hard in parallel / distributed systems?. A brief history of what people have done. CS539. Prof. Carolina Ruiz. Department of Computer Science . (CS). & Bioinformatics and Computational Biology (BCB) Program. & Data Science (DS) Program. WPI. Most figures and images in this presentation were obtained from Google Images. Corey . Pentasuglia. Masters Project. 5/11/2016. Examiners. Dr. Scott . Spetka. Dr. . Bruno . Andriamanalimanana. Dr. Roger . Cavallo. Masters Project Objectives. Research DML (Distributed Machine Learning). Dan Roth. University of Illinois, Urbana-Champaign. danr@illinois.edu. http://L2R.cs.uiuc.edu/~danr. 3322 SC. 1. CS446: Machine Learning. Tuesday, Thursday: . 17:00pm-18:15pm . 1404 SC. . Office hours: . The Desired Brand Effect Stand Out in a Saturated Market with a Timeless Brand Er. . . Mohd. . Shah . Alam. Assistant Professor. Department of Computer Science & Engineering,. UIET, CSJM University, Kanpur. Agenda. What is Machine Learning?. How Machine learning . is differ from Traditional Programming?. Abid M. Malik. Meifeng. Lin (PI). Collaborators: Amir . Farbin. (UT) , Jean . Roch. ( CERN). Computer Science and Mathematic Department. Brookhaven National Laboratory (BNL). Distributed ML for HEP.
Download Document
Here is the link to download the presentation.
"CS239-Lecture 16 Distributed Machine Learning"The content belongs to its owner. You may download and print it for personal use, without modification, and keep all copyright notices. By downloading, you agree to these terms.
Related Documents