PPT-Machine Learning with MapReduce

Author : tatiana-dople | Published Date : 2016-05-19

KMeans Clustering 3 How to MapReduce KMeans Given K assign the first K random points to be the initial cluster centers Assign subsequent points to the closest

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Machine Learning with MapReduce: Transcript

KMeans Clustering 3 How to MapReduce KMeans Given K assign the first K random points to be the initial cluster centers Assign subsequent points to the closest cluster using the supplied distance measure. edu Sang Kyun Kim skkim38stanfordedu YiAn Lin ianlstanfordedu YuanYuan Yu yuanyuanstanfordedu Gary Bradski 8727 garybradskigmail Andrew Y Ng angcsstanfordedu Kunle Olukotun kunlecsstanfordedu CS Department Stanford University 353 Serra Mall Stanford Spring . 2013. Rong. Jin. 2. CSE847 Machine Learning. Instructor: . Rong. Jin. Office Hour: . Tuesday 4:00pm-5:00pm. TA, . Qiaozi. . Gao. , . Thursday 4:00pm-5:00pm. Textbook. Machine Learning. The Elements of Statistical Learning. 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. 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. By . Yufei. Tao, . Wenqing. . Lin, . Xiaokui. . Xia. Edited by Tuval Rotem. First topic:. What is MapReduce. But first…. Regular day at work. You’re doing your regular work while suddenly your boss, . 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.. 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. : Simplified Data Processing on Large Clusters . Jeff Dean, Sanjay . Ghemawat. , Google, OSDI 2004. Slides based on those by . authors and other online sources. Motivation. Large . scale data processing. 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: . ”. Cathy O’Neil & Rachel . Schutt. , 2013. R & Hadoop. Compute squares. 2. R. # create a list of 10 integers. ints. <- 1:10. # equivalent to . ints. <- c(1,2,3,4,5,6,7,8,9,10). # compute the squares. An Overview of Machine Learning Speaker: Yi-Fan Chang Adviser: Prof. J. J. Ding Date : 2011/10/21 What is machine learning ? Learning system model Training and testing Performance Algorithms Machine learning (CS725). Autumn 2011. Instructor: . Prof. . Ganesh. . Ramakrishnan. TAs: . Ajay Nagesh, Amrita . Saha. , . Kedharnath. . Narahari. The grand goal. From the movie . 2001: A Space Odyssey. (1968). Outline. 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?.

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