Lecture

Right Arrow

SEARCH COURSES / LECTURES

Left Arrow

Artificial Intelligence (Fall 2010) (M-I-T)

(23 Lectures Available)

S# Lecture Course Institute Instructor Discipline
1
  • Lecture 10: Introduction to Learning, Nearest Neighbors (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
2
  • Lecture 11: Learning: Identification Trees, Disorder (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
3
  • Lecture 12A: Neural Nets (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
4
  • Lecture 12B: Deep Neural Nets (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
5
  • Lecture 13: Learning: Genetic Algorithms (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
6
  • Lecture 14: Learning: Sparse Spaces, Phonology (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
7
  • Lecture 15: Learning: Near Misses, Felicity Conditions (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
8
  • Lecture 16: Learning: Support Vector Machines (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
9
  • Lecture 17: Learning: Boosting (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
10
  • Lecture 18: Representations: Classes, Trajectories, Transitions (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
11
  • Lecture 19: Architectures: GPS, SOAR, Subsumption, Society of Mind (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
12
  • Lecture 1: Introduction and Scope (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
13
  • Lecture 21: Probabilistic Inference I (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
14
  • Lecture 22: Probabilistic Inference II (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
15
  • Lecture 23: Model Merging, Cross-Modal Coupling, Course Summary (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
16
  • Lecture 2: Reasoning: Goal Trees and Problem Solving (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
17
  • Lecture 3: Reasoning: Goal Trees and Rule-Based Expert Systems (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
18
  • Lecture 4: Search: Depth-First, Hill Climbing, Beam (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
19
  • Lecture 5: Search: Optimal, Branch and Bound, A* (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
20
  • Lecture 6: Search: Games, Minimax, and Alpha-Beta (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
21
  • Lecture 7: Constraints: Interpreting Line Drawings (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
22
  • Lecture 8: Constraints: Search, Domain Reduction (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences
23
  • Lecture 9: Constraints: Visual Object Recognition (M-I-T)
Artificial Intelligence (Fall 2010) (M-I-T) MIT Prof. Patrick Henry Winston Applied Sciences