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    CMPS 470, Spring 2008 Syllabus

    Contact Information

    Course Information

      In this course the student will be presented with an overview of the Machine Learning. We will introduce the topic and study a selection of techniques. The class will be presented using a both a mix of theory, exercises and programming. Machine Learning is an interesting topic, and our book covers a broad spectrum of concepts and algorithms. We will be studying a selection of them and write programs that apply these concepts and algorithms. Also, each student should get a USB thumb drive in order to save work and software that may be provided for the class. 

    Course Objectives

      The objectives of this course are for the student to become familiar with the ideas and concepts of machine learning and to able to apply them to both control/game playing and classification problems. This course is intended to teach the student to recognize what type of approach/approaches are needed for a given task and provide a background for designing and implementing the software to solve that task.


      Textbook: Machine Learning; Tom M. Mitchell


    Reference books include: Artificial Intelligence A guide to Intelligent Systems; Second Edition; Michael Negnevitsky

    Course Outline/Schedule (Subject to change)

    • Introduction Machine Learning
      • Terms
        • Knowledge
        • Learning
        • Understanding
      • Tasks
        • Control
        • Classification
      • Approach to problem solving
      • Quiz 1
    • Concept Learning
      • If then eliminate
      • Candidate Elimination Algorithm
      • Homework 1
      • Quiz 2
    • Decision Tree Learning
      • Entropy based algorithm
        • Concepts
        • Setting up code
      • Program 1
      • Quiz 3
    • Simulated Annealing
      • Relation ship to annealing in metals
      • Algorithm
      • Program 2
        • Dijkstra’s shortest path algorithm
        • Traveling Salesman
    • Genetic Algorithms
      • Basics/Terms
        • Survival of the fittest
        • Natural Selection
        • Population
        • Chromosomes
        • Genes
        • Breeding
          • Parent Selection
          • Crossover
          • Mutation
      • Solving a problem using a GA
      • GA algorithms
        • Classic
        • Elite
      • Quiz 4
      • Program 3
    • Clustering
      • What is clustering?
      • Deterministic/Non-Deterministic
      • Radial Basis algorithm
      • Program 4
      • Quiz 5
    • Neural Networks
      • Perceptrons
        • Program 5
      • Multi-layer networks
        • Feed-forward
        • Backpropagation
      • Self-Organizing Feature Maps
        • Program 6
      • Quiz 6
    • Reinforcement Learning
      • Cause and effect relationships
      • Delayed Reward
        • Q learning
        • Program 7
        • Quiz 7

Machine Learning Home Pat’s Home Page

Machine Learning Home Pat’s Home Page