PPT-CS 446: Machine Learning

Dan Roth University of Illinois UrbanaChampaign danrillinoisedu httpL2Rcsuiucedudanr 3322 SC 1 CS446 Machine Learning Tuesday Thursday 1700pm1815pm 1404 SC Office hours . AN TA YL OR GUCC PO LO RALP LA UREN LA OST MICHAEL KO RS 36 37 KI O 37 37 36 36 36 35 34 34 34 34 33 33 33 32 32 30 30 30 29 29 28 28 27 27 27 26 26 26 262 GH B AS CO BA TH BOD Y WO RK BLDG 13 BLDG 31 REEBOK GAP OUTL ET BLDG 1 21 NE BA LANC HF BLD 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. Jimmy Lin and Alek . Kolcz. Twitter, Inc.. Presented by: Yishuang Geng and Kexin Liu. 2. Outline. •Is twitter big data? . •How . can machine learning help twitter?. •Existing challenges?. •Existing literature of large-scale learning. 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. Dan Roth. University of Illinois, Urbana-Champaign. danr@illinois.edu. http://L2R.cs.uiuc.edu/~danr. 3322 SC. CS446: Machine Learning. What do you need to know:. . Theory of Computation. Probability Theory. Geoff Hulten. Why do people Attack Systems?. Crime, espionage. For fun. To make money. Making Money off of Abuse. Driving traffic. Compromising personal information. Compromising computers. Boosting content. 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 Bahrudin Hrnjica, MVP. Agenda. Intro to ML. Types of ML. dotNET and ML-tools and libraries. Demo01: ANN with C#. Demo02: GP with C#. .NET Tools – Acord.NET, GPdotNET. Summary. Machine Learning?. method of teaching computers to make predictions based on data.. Page 46 L istening to the voice of customers plays a prominent role in a customer-centric business strategy. But with the business environment’s increased complexity and dynamism for a customer-    \n!"###$% \r "&\r'()$)
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