Conclusion

• Take Home Points
  1. The five learning outcomes including knowledge representation, machine learning and search spaces.
  2. The Evaluation is CW1 20%, CW2 30%, and the exam 50%.
  3. AI is a big field and there are jobs if you understand it.
  4. In this class, you need to program in Java.
  5. You should already know all of the Java stuff I showed (except maybe arrays) and some of the other Java stuff.
• Reading: For this lecture you can look at Russel and Norvig's introductory chapter. Other people think about AI differently than I do, and they have a valid stance. This won't really be on the exam.
• Reading: For the next lecture you can look at the Binary Classification wiki , and the Linear Classifier wiki .