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Applied Data Analysis and Machine Learning

  • Applied Data Analysis and Machine Learning

About the course

  • Teaching schedule with links to material
  • Teachers and Grading
  • Textbooks

Review of Statistics with Resampling Techniques and Linear Algebra

  • 1. Elements of Probability Theory and Statistical Data Analysis
  • 2. Linear Algebra, Handling of Arrays and more Python Features

From Regression to Support Vector Machines

  • 1. Linear Regression, basic Elements
  • 2. Resampling Methods
  • 3. Ridge and Lasso Regression
  • 4. Logistic Regression
  • 5. Support Vector Machines, overarching aims

Decision Trees, Ensemble Methods and Boosting

  • 1. Decision trees, overarching aims
  • 2. Ensemble Methods: From a Single Tree to Many Trees and Extreme Boosting, Meet the Jungle of Methods

Dimensionality Reduction

  • 1. Basic ideas of the Principal Component Analysis (PCA)

Deep Learning Methods

  • 1. Neural networks
  • 2. Building a Feed Forward Neural Network
  • 3. Solving Differential Equations with Deep Learning
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Teaching schedule with links to materialΒΆ

This course will be delivered in a hybrid mode, with online lectures and on site or online laboratory sessions.

  1. Four lectures per week, Fall semester, 10 ECTS. The lectures will be fully online. The lectures will be recorded and linked to this site and the official University of Oslo website for the course;

  2. Two hours of laboratory sessions for work on computational projects and exercises for each group. Due to social distancing, at most 15 participants can attend. There will also be fully digital laboratory sessions for those who cannot attend;

  3. Three projects which are graded and count 1/3 each of the final grade;

  4. A selected number of weekly assignments;

  5. The course is part of the CS Master of Science program, but is open to other bachelor and Master of Science students at the University of Oslo;

  6. The course is offered as a FYS-MAT4155 (Master of Science level) and a FYS-MAT3155 (senior undergraduate) course;

  7. Videos of teaching material are available via the links at https://compphysics.github.io/MachineLearning/doc/web/course.html

  8. Weekly emails with summary of activities will be mailed to all participants;

Applied Data Analysis and Machine Learning Teachers and Grading

By Morten Hjorth-Jensen
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