Plans for week 39

Dear all and welcome to a new week with FYS-STK3155/4155. We hope you've had a pleasant weekend.

The plans for this week are tentatively as follows:

Material for the active learning sessions on Tuesday and Wednesday

• Discussions on how to structure your report for the first project
• Exercise for week 39 on how to write the abstract and the introduction of the report and how to include references. See link below.
• Link to the exercise
• Work on project 1, in particular resampling methods like cross-validation and bootstrap. For more discussions of project 1, chapter 5 of Goodfellow et al is a good read, in particular sections 5.1-5.5 and 5.7-5.11.

These sections summarize neatly what we have done till now and point to what is coming with respect to deep learning.

• A general guideline can be found at https://github.com/CompPhysics/MachineLearning/blob/master/doc/Projects/EvaluationGrading/EvaluationForm.md.

Material for the lecture on Thursday September 28

• Repetition of Logistic regression equations and classification problems and discussion of Gradient methods. Examples on how to implement Logistic Regression and discussion of stochastic gradient descent
• Stochastic Gradient descent with examples and automatic differentiation. This will be the topic next week as well. During week 40 we will also start our discussions of deep learning methods and neural networks
• Readings and Videos:
  • For a good discussion on gradient methods, we would like to recommend Goodfellow et al section 4.3-4.5 and sections 8.3-8.6. We will come back to the latter chapter in our discussion of Neural networks as well. We start discussing neural networks in week 40
  • Lecture material this week
  • Video on gradient descent
  • Video on stochastic gradient descent

Best wishes to you all,

Adam, Daniel, Fahimeh, Ida, Karl Henrik, Mia, and Morten