Week 08

Feed-forward neural networks and back-propagation

Interactive session, Thursday March 7

Discussion slides

Weekly lecture:

Slides

Video Recordings:

  1. Feed-forward neural networks (Multi-layer Perceptrons)
  2. Matrix representations
  3. The Back-propagation Algorithm
    1. The basics
    2. Linear Regression
    3. The first layer
    4. Logistic Regression
    5. Multi-class classification
  4. Finer Details
  5. Evaluation: Precision, Recall and F1

Readings

  • Marsland, Machine Learning
    • Chapter 4 "The Multi-layer Perceptron", everything, except
      • (for now) 4.2.6 Picking up momentum
      • the technical details of 4.6 Deriving Back-propagation,
        What you have to know here, is covered by the lectures.
  • Speech and Language Processing. Daniel Jurafsky & James H. Martin.
    • Chapter 7, sections 7.1, 7.2, 7.3, 7.4, 7.5
  • If you feel that your skills with vectors, matrices and tensors need some refreshment, check out our linear algebra cheat-sheet.

Weekly exercises

Published Mar. 1, 2024 1:52 PM - Last modified Mar. 20, 2024 5:27 PM