PPT-Machine Learning

Author : sherrill-nordquist | Published Date : 2015-09-28

Lecture 10 Decision Trees G53MLE Machine Learning Dr Guoping Qiu 1 Trees Node Root Leaf Branch Path Depth 2 Decision Trees A hierarchical data structure that

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Machine Learning: Transcript


Lecture 10 Decision Trees G53MLE Machine Learning Dr Guoping Qiu 1 Trees Node Root Leaf Branch Path Depth 2 Decision Trees A hierarchical data structure that represents data by implementing a divide and conquer strategy . Lecture 5. Bayesian Learning. G53MLE | Machine Learning | Dr Guoping Qiu. 1. Probability. G53MLE | Machine Learning | Dr Guoping Qiu. 2. . 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. 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. http://hunch.net/~mltf. John Langford. Microsoft Research. Machine Learning in the present. Get a large amount of labeled data . . where . . Learn a predictor . Use the predictor.. The Foundation: Samples + Representation + Optimization. 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. 1. Sandia . National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of  Sandia, LLC, a wholly owned subsidiary of Honeywell International,  Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.  SAND2017-6417C. 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). 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. 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.. (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. Nicolas . Borisov. . 1,. *, Victor . Tkachev. . 2,3. , Maxim Sorokin . 2,3. , and Anton . Buzdin. . 2,3,4. . 1. Moscow . Institute of Physics and Technology, 141701 Moscow Oblast, Russia. 2. OmicsWayCorp. Gihyuk Ko. PhD Student, Department of Electrical and Computer Engineering. Carnegie Mellon University. November. 14, 2016. *some slides were borrowed from . Anupam. . Datta’s. MIT Big . Data@CSAIL. Ryan Ma . Background and Purpose of the Project. Aerodynamic analysis is one of the most crucial traits of a vehicle. It affects the fuel consumption of a car. . The shape of the car significantly affects the aerodynamic performances, which includes the lift and the drag. .

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