Course Syllabus

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Deep Learning

Elisabetta Fersini

Inglese

  • Background concepts
  • Training Deep Networks:
    * Objective functions
    * Activation Functions
    * Regularization
    * Gradient-based optimization
  • Focus on Deep Networks:
    * Autoencoders
    * Variational Autoencoders
  • Practical Methodology:
    * Performance Metrics and baseline models
    * Selecting hyper-parameters
  • Deep Learning in Practice: Tools, Tips and Tricks

2 CFU, 16 ore

Luglio 2024

Export

Deep Learning

Elisabetta Fersini

English

  • Background concepts
  • Training Deep Networks:
    * Objective functions
    * Activation Functions
    * Regularization
    * Gradient-based optimization
  • Focus on Deep Networks:
    * Autoencoders
    * Variational Autoencoders
  • Practical Methodology:
    * Performance Metrics and baseline models
    * Selecting hyper-parameters
  • Deep Learning in Practice: Tools, Tips and Tricks

2 CFU, 16 hours

July 2024

Enter

Key information

Field of research
INF/01
ECTS
2
Term
Annual
Activity type
Optional
Course Length (Hours)
16

Staff

    Teacher

  • EF
    Elisabetta Fersini

Enrolment methods

Manual enrolments
Self enrolment (Student)