Introduction to Machine Learning; Classification of learning: unsupervised and supervised learning, connectionist learning, reinforcement learning, machine discovery; Supervised learning: Information theoretic decision tree learner, best current hypothesis search, candidate elimination (version space) algorithm, learning in the first order Horn clause representation, inductive logic programming, applications; Unsupervised learning: hierarchical clustering, category utility, incremental and non-incremental algorithms for hierarchical clustering, applications; Connectionist learning: introduction to neural networks, Feed forward and recurrent networks, perception, multilayer feed forward networks, backpropagation algorithm for training a feed forward network, applications; Genetic algorithms: genetic operators, fitness function, genetic algorithm in supervised learning framework, applications.

Course Type | Major |
---|---|

Credit Hour | 3 |

Lecture Hour | 45 |

- Be able to articulate key concepts and principles in Machine learning.
- Be able to articulate and model problems given an understating of representational issues and abstraction in machine learning.
- Be able to explain and analyze models and results making use of theoretical principles and the limitations of generalization in machine learning.
- Make use of the algorithmic theory of machine learning in problem analysis and model selection.
- Understand and apply the maximum likelihood principle and explain algorithmic implications in modeling and problem solving.
- Be able to use a variety of algorithmic techniques in machine learning.
- Be able to choose and use a variety of machine learning protocols in different situations.

Biweekly Quiz, One Midterm Exam, One Final Exam, Project

Letter Grade | Marks | Grade Point |
---|---|---|

A | 90 - 100 | 4.00 |

A- | 85 - 89 | 3.70 |

B+ | 80 - 84 | 3.30 |

B | 75 - 79 | 3.00 |

B- | 70 - 74 | 2.70 |

C+ | 65 - 69 | 2.30 |

C | 60 - 64 | 2.00 |

C- | 55 - 59 | 1.70 |

D+ | 50 - 54 | 1.30 |

D | 45 - 49 | 1.00 |

F | 00 - 44 | 0.00 |