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Level 5 Diploma in Cyber Security

Evaluating trained models: train vs. test performance, overfitting and underfitting, proposing improvements

CYB503 · Artificial Intelligence — Week 7 of 16

CourseCYB503
Week7 of 16
SemesterI
TutorOnline in the course chat

This week’s topics

Evaluating trained models: train vs. test performance, overfitting and underfitting, proposing improvements

  1. The performance of trained neural network models with reference to the training-test gap

What you will be able to do

  • 3.4 Evaluate the performance of trained neural network models with reference to the training-test gap.

Activity

Seminar, guided reading and a short written task: evaluate the performance of trained neural network models with reference to the training-test gap.

Study materials

The teaching notes, exercises and videos of this week are in the student portal. Your portal is set up as soon as you receive final acceptance, so you can open them before the semester starts.
Week 6Midterm
Course chat

Admitted students ask questions on this week’s page in the student portal: an AI assistant trained on the course answers first, and during the course’s timetabled classes Connect to your tutor brings your tutor into the chat, who may start a call if needed.

Open this week in the portal
Course plan
  • Week 1: History of AI (Babbage, the Turing test), symbolic AI vs. m…
  • Week 2: Machine learning approaches: linear and logistic regression…
  • Week 3: Neural network preliminaries: biological inspiration, unive…
  • Week 4: Training neural networks: loss functions, SGD, learning rat…
  • Week 5: Neural network architectures: dense, convolutional, transfo…
  • Week 6: Building networks in PyTorch or TensorFlow/Keras; training …
  • Week 7: Evaluating trained models: train vs. test performance, over…
  • Midterm: Midterm evaluation
  • Week 9: Deep generative models: variational autoencoders, normalisi…
  • Week 10: CLIP and image/video generation
  • Week 11: AI in cyber security: traffic scanning and email filtering
  • Week 12: Applying Artificial Intelligence in practice: case studies
  • Week 13: Assignment workshop: research, planning and referencing
  • Week 14: Assignment workshop: drafting, feedback and improvement
  • Week 15: Review and coursework completion
  • Final: Final assessment and submission
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