Revision as of 17:33, 22 May 2017

Starting Places

• AITopics.org
• Educational Advances in AI (EAAI)
• Model AI Assignments

General

• Texts:
  • Stuart Russell, Peter Norvig. Artificial Intelligence: a modern approach

Machine Learning

• Texts:
  • Christopher Bishop. Pattern Recognition and Machine Learning
  • Kevin Murphy. Machine Learning: A Probabilistic Perspective
  • David Barber. Probabilistic Reasoning and Machine Learning (Barber's free PDF version)
  • Tom Mitchell. Machine Learning
  • Ethem Alpaydin. Introduction to Machine Learning
  • Statistical Learning:
    • Trevor Hastie, Robert Tibshirani, and Jerome Friedman. The Elements of Statistical Learning
    • Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani. An Introduction to Statistical Learning with Applications in R (RStudio software for labs)
  • Reinforcement Learning:
    • Richard Sutton and Andrew Barto. Reinforcement Learning: an introduction
    • Csaba Szepesvári. Algorithms for Reinforcement Learning
    • Marco Wiering and Martijn van Otterlo. Reinforcement Learning: State-of-the-Art
• Online resources:
  • Andrew Ng's free online Coursera Machine Learning course
  • UC Irvine Machine Learning Repository
  • Kaggle datasets
  • RStudio software for labs
  • Weka Java-based Data Mining software and Ian Witten and Eibe Frank. Data Mining: Practical Machine Learning Tools and Techniques
  • Model AI Assignments
• Recommendations:
  • Quora "How do I learn machine learning?" answers
  • Joseph Misiti's Machine Learning book recommendations

Neural Network Learning

• Textbooks
  • Neural network basics
  • Deep learning
• Websites
• Software
• Hardware