Concept learning Maria Simi, 2011/2012 Machine Learning, Tom

Introduction to machine learning  Introduction to machine learning  When appropriate and when not appropriate  Task definition  Learning methodology: design, experiment, evaluation  Learning issues: representing hypothesis  Learning paradigms  Supervised learning  Unsupervised learning  Reinforcement learning  Next week …
Bibliography  Machine Learning, Tom Mitchell, Mc Graw-Hill International Editions, 1997 (Cap 2).

PPT - Concept Learning PowerPoint Presentation, free download - ID:1821850

Bulletin - 2011-2012 by Columbia Engineering School - Issuu

MACHINE LEARNING (Mcgraw-Hill by Mitchell, Thom

MACHINE LEARNING (Mcgraw-Hill by Mitchell, Thom

PPT - A Granular Computing Paradigm for Concept Learning PowerPoint Presentation - ID:2120257

When the Chips are Down: Learning from the HR Headlines

Chapter 2 — Concept Learning — Part 1, by Pralhad Teggi

Deep Learning for Information Retrieval

Open Life Sciences

Materials Data toward Machine Learning: Advances and Challenges

2013 Annual Report: 2013 Continuing Professional Development Gap Analysis and Needs Assessment Initiative