Week 07:
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1. Study for the Midterm Exam.
   
   
2. Take the Midterm Exam.
   
   
3. Listen to the following interview:
   • Audio: Quirks and Quarks: Artificial Intelligence Wins Gold (19 FEB 2011) (9 min 46 sec) interview of Geoffrey Hinton hosted by Bob McDonald.
   
   Reference: Quirks and Quarks: Artificial Intelligence Wins Gold (19 FEB 2011).
   
   Read the following article:
   • The Triumph Of Deep Learning (Page 1 of 2)
   • The Triumph Of Deep Learning (Page 2 of 2)
   
   Watch the following tutorial on Deep Learning from JUL 2009:
   • A tutorial on Deep Learning (JUL 2009) by Geoffrey Hinton:
     
     • Part 1 (1 hour 34 min 53 sec)
     • Part 2 (1 hour 31 min 54 sec)
   
   Read the following papers:
   • A fast learning algorithm for deep belief nets (2006) by Geoffrey Hinton, Simon Osindero, and Yee-Whye Teh
   • Deep learning with COTS HPC systems (2013) by Adam Coates, Brody Huval, Tao Wang, David J. Wu, Andrew Y. Ng, and Bryan Catanzaro
   
   Play with the following model:
   • Hinton's Neural Network Simulation (Generative)
   
   Reference: Explanation of the digit movies.
   
   (Optional) Watch the following video:
   • Recent Developments in Deep Learning (19 MAR 2010) by Geoffrey Hinton from Google Tech Talks (1 hour 5 min 18 sec).
   
   
4. Work on your Research Project.
   
   
5. Read the following pages from Artificial Intelligence: A Modern Approach, Third Edition (cited as AIMA):
   • Required: 0 Pages
     
     
   • Optional: 71 Pages ... Note: This reading will be required in Week 08.

     Order	Topic	Book	Section	Page Numbers	Pages	Presentations
     1.	Logical Agents	AIMA	Chapter 7:	Page 234-275	(42 Pages)	Logic and Propositional Logic, Propositional Inference, Propositional Agents, and Logic
     2.	First-Order Logic	AIMA	Chapter 8:	Page 285-313	(29 Pages)	First-Order Logic and Logic

     
     
   Reference: University of California, Berkeley's CS 188: Introduction to Artificial Intelligence (Fall 2005) by Stuart Russell
   Reference: Stanford University's CS221: Artificial Intelligence: Principles and Techniques (Autumn 2012-2013) by Percy Liang