Continual Learning Course
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Continual Learning: On Machines that can Learn Continually
Background
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Prerequisites
🛠
Tools & Setup
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Course Details
Lectures
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Introduction & Motivation
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Understanding Catastrophic Forgetting
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Scenarios & Benchmarks
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Evaluation & Metrics
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Methodologies [Part 1]
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Methodologies [Part 2]
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Methodologies [Part 3], Applications & Tools
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Frontiers in Continual Learning
Invited & Extra Lectures
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Avalanche Dev Day
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Invited Talks
Resources
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Course Materials
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Additional Material
About Us
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Your Instructor
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Teaching Assistants
Useful Links
Avalanche
Forum
Colab
Wiki
Open World Lifelong Learning Course
ContinualAI
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Prerequisites
Things you Should Know Before Enrolling
This course has been designed for Graduate and PhD Students that have never been exposed to Continual Learning. However, it assumes basic knowledge in Computer Science (Bachelor level) and Machine Learning. In particular we assume basic knowledge in Deep Learning.
For students do not have this background we suggest to follow at least an introductory Machine Learning course such the one offered by Andrew Ng at Cursera.
We also assume basic hands-on knowledge about:
  • Anaconda, Python and PyCharm
  • Python Notebooks
  • Google Colaboratory
  • Git and GitHub
  • PyTorch
Make sure you learn the basics of these tools and languages as they will be used extensively across the course.
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Continual Learning: On Machines that can Learn Continually
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Tools & Setup
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