everything.study
COMP 551

Applied Machine Learning

4 credits · Undergraduate / Professional

Winter2026

Topics

  • Linear regression and classification
  • Gradient-based optimization
  • Deep neural networks
  • Dimensionality reduction
  • Clustering

Readings

  • Probabilistic Machine Learning: An Introduction
    Kevin P. Murphy · Reference; no required textbook
  • Pattern Recognition and Machine Learning
    Christopher M. Bishop · Reference; no required textbook
  • Deep Learning
    Ian Goodfellow,Yoshua Bengio and Aaron Courville · Reference; no required textbook
  • Machine Learning: A Probabilistic Perspective
    Kevin P. Murphy · Reference; no required textbook
  • The Elements of Statistical Learning
    Trevor Hastie,Robert Tibshirani and Jerome Friedman · Related reference
  • Information Theory,Inference,and Learning Algorithms
    David J. C. MacKay · Related reference
  • Bayesian Reasoning and Machine Learning
    David Barber · Related reference
  • Understanding Machine Learning: From Theory to Algorithms
    Shai Shalev-Shwartz and Shai Ben-David · Related reference
  • Foundations of Machine Learning
    Mehryar Mohri,Afshin Rostamizadeh and Ameet Talwalkar · Related reference
  • Dive into Deep Learning
    Aston Zhang,Zachary Lipton,Mu Li and Alexander J. Smola · Related reference
  • Mathematics for Machine Learning
    Marc Peter Deisenroth,A. Aldo Faisal and Cheng Soon Ong · Related reference
  • A Course in Machine Learning
    Hal Daumé III · Related reference
  • Hands-on Machine Learning with Scikit-Learn and TensorFlow
    Aurélien Géron · Related reference
Sources
Catalogue variants