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Introduction to Machine Learning: Concepts and Applications

Dive into the world of machine learning with Ahmed Elgammal from Rutgers University. Learn about the basics, techniques, and applications of this field, including its overlap with statistics and practical uses in various industries. Explore the development of tractable algorithms for inference problems and the wide spectrum of applications such as search engines, medical diagnosis, and more.

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Introduction to Machine Learning: Concepts and Applications

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  1. CS 536: Machine Learning Fall 2005 Ahmed Elgammal Dept of Computer Science Rutgers University CS 536 – Ahmed Elgammal - - 1

  2. Outlines • Class policies • What is machine learning • Some basics CS 536 – Ahmed Elgammal - - 2

  3. Machine Learning ? CS 536 – Ahmed Elgammal - - 3

  4. What is machine learning (From Wikipedia) • Machine learning is an area of artificial intelligence concerned with the development of techniques which allow computers to "learn". More specifically, machine learning is a method for creating computer programs by the analysis of data sets. Machine learning overlaps heavily with statistics, since both fields study the analysis of data, but unlike statistics, machine learning is concerned with the algorithmic complexity of computational implementations. Many inference problems turn out to be NP-hard so part of machine learning research is the development of tractable approximate inference algorithms. • Machine learning has a wide spectrum of applications including search engines, medical diagnosis, detecting credit card fraud, stock market analysis, classifying DNA sequences, speech and handwriting recognition, game playing and robot locomotion. CS 536 – Ahmed Elgammal - - 4

  5. 5.1,3.5,1.4,0.2,Iris-setosa • 4.9,3.0,1.4,0.2,Iris-setosa • 4.7,3.2,1.3,0.2,Iris-setosa • 4.6,3.1,1.5,0.2,Iris-setosa • 5.0,3.6,1.4,0.2,Iris-setosa • 7.0,3.2,4.7,1.4,Iris-versicolor • 6.4,3.2,4.5,1.5,Iris-versicolor • 6.9,3.1,4.9,1.5,Iris-versicolor • 5.5,2.3,4.0,1.3,Iris-versicolor • 6.4,2.7,5.3,1.9,Iris-virginica • 6.8,3.0,5.5,2.1,Iris-virginica • 5.7,2.5,5.0,2.0,Iris-virginica • 5.8,2.8,5.1,2.4,Iris-virginica • 6.4,3.2,5.3,2.3,Iris-virginica CS 536 – Ahmed Elgammal - - 5

  6. Sources CS 536 – Ahmed Elgammal - - 6

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