DD2437/FDD3437 VT24 Artificial Neural Networks and Deep Architectures (annda124)

DD2437/FDD3437 VT24 Artificial Neural Networks and Deep Architectures (annda124)

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Course overview Course overview

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Course overview 122059  

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  Course information, scope and learning outcomes Course information, scope and learning outcomes       2

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  Assessment - what to do to pass the course Assessment - what to do to pass the course       3

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  Lectures, labs and partial exams (quizzes) - an overview Lectures, labs and partial exams (quizzes) - an overview       4

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  Lab review and report Lab review and report       5

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  Literature and extra resources Literature and extra resources       6

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  Past exams Past exams       8

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Lectures 1-4 Multi-layer perceptrons: learning and generalisation

Lectures 1-4 Multi-layer perceptrons: learning and generalisation Lectures 1-4 Multi-layer perceptrons: learning and generalisation

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Lectures 1-4 Multi-layer perceptrons: learning and generalisation 122060  

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  Content, lectures, ... 🧬       3

      context_module_sub_header 825081 0

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  L1 Course introduction and fundamental concepts L1 Course introduction and fundamental concepts       4

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  L2 From perceptron learning rule to backpropagation in feedforward networks - supervised learning L2 From perceptron learning rule to backpropagation in feedforward networks - supervised learning       5

      wiki_page 825083 0

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  L3 Generalization, regularization, model selection and validation L3 Generalization, regularization, model selection and validation       6

      wiki_page 825084 0

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  L4 Practical aspects of ANN approaches to pattern recognition problems L4 Practical aspects of ANN approaches to pattern recognition problems       7

      wiki_page 825085 0

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• Quiz

  Practice quiz on Perceptron Practice quiz on Perceptron       9

      quiz 825087 0

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• Quiz

  Practice quiz on Generalisation, regularisation Practice quiz on Generalisation, regularisation       10

      quiz 825088 0

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  Assessed work 📅       11

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  KS quiz 1 KS quiz 1 0     12

      assignment 825090 1

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  Lab 1a       13

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• Assignment

  Lab 1a - presentation Lab 1a - presentation 1     14

      assignment 825092 1

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• Assignment

  Lab 1a - very short report Lab 1a - very short report 1     15

      assignment 825093 1

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• Assignment

  Lab 1a - bonus Lab 1a - bonus 1     16

      assignment 825094 1

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  Lab 1b       17

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• Assignment

  Lab 1b - presentation Lab 1b - presentation 1     18

      assignment 825096 1

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• Assignment

  Lab 1b - very short report Lab 1b - very short report 1     19

      assignment 825097 1

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• Assignment

  Lab 1b - bonus Lab 1b - bonus 1     20

      assignment 825098 1

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Lectures 5-6 Competitive learning, self-organising maps

Lectures 5-6 Competitive learning, self-organising maps Lectures 5-6 Competitive learning, self-organising maps

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Module completed Module in progress Module locked

Lectures 5-6 Competitive learning, self-organising maps 122061  

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  Content, lectures, ... 🧬       3

      context_module_sub_header 825101 0

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• Page

  L5 Radial basis function networks and introduction to competitive learning L5 Radial basis function networks and introduction to competitive learning       4

      wiki_page 825102 0

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  L6 Self-organising maps L6 Self-organising maps       5

      wiki_page 825103 0

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• Quiz

  Practice quiz on CL, RBFs, SOMs and Hopfield nets Practice quiz on CL, RBFs, SOMs and Hopfield nets       7

      quiz 825105 0

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• Context Module Subheader

  Assessed work 📅       8

      context_module_sub_header 825106 0

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• Context Module Subheader

  Lab 2       9

      context_module_sub_header 825107 0

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• Assignment

  Lab 2 - presentation Lab 2 - presentation 1     10

      assignment 825108 1

  Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark completed Must mark this module item done in order to complete Marked completed Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
• Assignment

  Lab 2 - very short report Lab 2 - very short report 1     11

      assignment 825109 1

  Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark completed Must mark this module item done in order to complete Marked completed Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
• Assignment

  Lab 2 - bonus Lab 2 - bonus 1     12

      assignment 825110 1

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Lectures 7-8 Recurrent architectures and stochastic networks

Lectures 7-8 Recurrent architectures and stochastic networks Lectures 7-8 Recurrent architectures and stochastic networks

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Module completed Module in progress Module locked

Lectures 7-8 Recurrent architectures and stochastic networks 122062  

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  Content, lectures, ... 🧬       3

      context_module_sub_header 825113 0

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• Page

  L7 Hopfield networks, associative memories and introduction to stochastic networks (Boltzmann machines) L7 Hopfield networks, associative memories and introduction to stochastic networks (Boltzmann machines)       4

      wiki_page 825114 0

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• Page

  L8 Temporal processing with ANNs: feedforward vs recurrent network architectures L8 Temporal processing with ANNs: feedforward vs recurrent network architectures       5

      wiki_page 825115 0

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• Assignment

  KS quiz 2 KS quiz 2 0     8

      assignment 825118 1

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• Context Module Subheader

  Lab 3       9

      context_module_sub_header 825119 0

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• Assignment

  Lab 3 - presentation Lab 3 - presentation 1     10

      assignment 825120 1

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• Assignment

  Lab 3 - very short report Lab 3 - very short report 1     11

      assignment 825121 1

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• Assignment

  Lab 3 - bonus Lab 3 - bonus 1     12

      assignment 825122 1

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Lectures 9-10 Deep neural networks: principles, architectures and implementations

Lectures 9-10 Deep neural networks: principles, architectures and implementations Lectures 9-10 Deep neural networks: principles, architectures and implementations

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Module completed Module in progress Module locked

Lectures 9-10 Deep neural networks: principles, architectures and implementations 122063  

• Page

  L9 Deep learning fundamentals: general philosophy and a review of deep architectures L9 Deep learning fundamentals: general philosophy and a review of deep architectures       4

      wiki_page 825126 0

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• Page

  L10a Representation learning L10a Representation learning       5

      wiki_page 825127 0

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• Page

  L10b Representation learning and deep generative modelling L10b Representation learning and deep generative modelling       6

      wiki_page 825128 0

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• Context Module Subheader

  Resources 💾       8

      context_module_sub_header 825130 0

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• Quiz

  Practice quiz on Deep learning Practice quiz on Deep learning       9

      quiz 825131 0

  Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark completed Must mark this module item done in order to complete Marked completed Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
• Context Module Subheader

  Assessed work 📅       10

      context_module_sub_header 825132 0

  Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark completed Must mark this module item done in order to complete Marked completed Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
• Assignment

  KS quiz 3 KS quiz 3 0     11

      assignment 825133 1

  Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark completed Must mark this module item done in order to complete Marked completed Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
• Context Module Subheader

  Lab 4       12

      context_module_sub_header 825134 0

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• Assignment

  Lab 4 - presentation Lab 4 - presentation 1     13

      assignment 825135 1

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• Assignment

  Lab 4 - very short report Lab 4 - very short report 1     14

      assignment 825136 1

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• Assignment

  Lab 4 - bonus Lab 4 - bonus 1     15

      assignment 825137 1

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Course summary, past exams

Course summary, past exams Course summary, past exams

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  L11 Past exams, Q&A L11 Past exams, Q&A       1

      wiki_page 825138 0

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  [ Select module ] Course overview Lectures 1-4 Multi-layer perceptrons: learning and generalisation Lectures 5-6 Competitive learning, self-organising maps Lectures 7-8 Recurrent architectures and stochastic networks Lectures 9-10 Deep neural networks: principles, architectures and implementations Course summary, past exams

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