Syllabus for Part 2 of Nature of Code: "Intelligence and Learning" at ITP Spring 2017 Edit
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The Nature of Code Part 2 (Spring 2017)

Syllabus for Part 2 of Nature of Code: "Intelligence and Learning" at ITP Spring 2017

This syllabus is very much in progress. I'm drawing inspiration from this Coding Train community list of resources.

Class Info

Prerequisites?

Week 1 - Introduction (March 21/22)

Week 2 - Genetic Algorithms (March 28/29)

Week 3 - Classification and Regression (April 4/5)

  • Week 3 Notes
  • Week 3 Homework
  • What is Machine Learning
  • What is Supervised Learning
  • Classification and Regression
  • KNN
  • Linear Regression and Gradient Descent

Week 4 - Neural Networks (April 11/12)

  • Week 4 Notes
  • Perceptron
  • Multi-Layered Perceptron
  • inputs and outputs
  • Backpropogation
  • Training vs. Testing (MNIST data set)
  • What is "Deep Learning"?

Week 5 - Adding Tensorflow: Convolutional Neural Networks (April 18/19)

Week 6 - Recurrent Neural Networks, NeuroEvolution/Reinforcement Learning (April 25/26)

Week 7 - Project Presentations (May 2/3)

Policies

  • Submit assignments by the evening before class to the extent possible.
  • Come prepared with questions.
  • Put away screens during others' presentations.
  • Participate!
  • Document!
  • Grading:
    • 40% Class Participation
    • 40% Quality of assignments
    • 20% Final project
  • For a 2-point class, 2 or more unexcused absences is grounds for failure.