AI & ML Reference Material

This page will host materials covering a variety of AI & ML algorithms and methods.

Natural Language Processing (NLP)

• NLP fundamentals
  • Stanford NLP lecture videos by Professors Dan Jurafski, Chris Manning
  • NLP overview lecture from Carnegie Mellon course 'Graduate Artificial Intelligence'
• Applying NLP
  • Python Natural Language Toolkit Book
  • Cortical.io API demos
    • navigate to Quickstart -> REST API -> Interactive API

Reinforcement Learning

• Classic AI & ML
  • UC Berkeley CS188 lecture video
  • Relevant sections of Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig
  • A Survey of Reinforcement Learning
  • Reinforcement Learning in Robotics: A Survey - Has a practical, real-world perspective.
  • Reinforcement Learning: A Survey - Old, but comprehensive.
  • The popular "TD-gammon" example
  • On the differences between TD(lambda) and Q-learning
  • Our presentation slides point to some useful papers as well.
• In the brain
  • Neural Basis of Reinforcement Learning and Decision Making
  • Reinforcement Learning, High-Level Cognition, and the Human Brain
  • Hierarchical reinforcement learning and decision making
  • Temporal Difference Models and Reward-Related Learning in the Human Brain
  • Preference by Association: How Memory Mechanisms in the Hippocampus Bias Decisions