Topic outline

• General

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  • DAT112 Neural Network Programming (Apr 2024)

    This six-week class will introduce neural network programming concepts, theory and techniques. The class material will begin at an introductory level, intended for those with no experience with neural networks, eventually covering intermediate-to-advanced concepts.
    

    Classes will be held, April 23 - May 30, Tuesdays and Thursdays, 11:00am - 12:00pm.

    Format: Virtual

    Teacher: Erik Spence

    Start date: 23 Apr 2024

    End date: 30 May 2024

    Data Science Credits: 16

    Events:

    DAT112: Lecture 1 - Tuesday, 23 April, 11:00 AM » 12:00 PM

    DAT112: Lecture 2 - Thursday, 25 April, 11:00 AM » 12:00 PM

    DAT112: Lecture 3 - Tuesday, 30 April, 11:00 AM » 12:00 PM

    A full list of course events can be found here.
  • 

    Forum

    Announcements Forum

• Lectures
  • • 1. Introduction
      • intro_I.pdf
      • lecture1_code.tar.gz
  • • 2. Neural networks
      • intro_II.pdf
      • lecture2_code.tar.gz
      • mnist.pkl.gz
  • • 3. Frameworks
      • frameworks.pdf
      • lecture3_code.tar.gz
  • • 4. Convolutional neural networks
      • CNNs.pdf
      • lecture4_code.tar.gz
  • 

    File

    5. Image classification File
  • • 6. Variational autoencoders
      • MNIST_VAE.mpg
      • mnist_vae.py
      • VAEs.pdf
  • • 7. Generative adversarial networks
      • GANs.pdf
      • MNIST_gan.mpg
      • MNIST_gan.py
  • • 8. Diffusion models
      • DM.pdf
      • lecture8_code.tar.gz
  • • 9. Graph neural networks
      • GNNs.pdf
      • lecture9_code.tar.gz
  • • 10. Recurrent neural networks
      • lecture10_code.tar.gz
      • RNNs.pdf
  • • 11. Sequence-to-sequence networks
      • lecture11_code.tar.gz
      • S2S.pdf
  • • 12. Attention networks
      • Attention.pdf
      • lecture12_code.tar.gz

• Recordings
  • 

    File

    1. Introduction File
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    File

    2. Neural networks File
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    File

    3. Frameworks File
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    File

    4. Convolutional neural networks File
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    File

    5. Image classification File
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    File

    6. Variational autoencoders File
  • 

    File

    7. Generative adversarial networks File
  • 

    File

    8. Diffusion models File
  • 

    File

    9. Graph neural networks File
  • 

    File

    10. Recurrent neural networks File
  • 

    File

    11. Sequence-to-sequence networks File
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    File

    12. Attention networks File

• Assignments
  • 

    Assignment

    Assignment 1

    Opened: Thursday, 2 May 2024, 11:30 AM

    Due: Thursday, 9 May 2024, 11:59 PM
  • 

    Assignment

    Assignment 2

    Opened: Wednesday, 15 May 2024, 12:00 AM

    Due: Thursday, 23 May 2024, 11:59 PM
  • 

    Assignment

    Assignment 3

    Opened: Tuesday, 28 May 2024, 11:00 AM

    Due: Tuesday, 4 June 2024, 11:59 PM