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Brain Computation: A Hands-on Guidebook

Chapter 1. Introduction
Chapter 2. Neural Modeling and Analysis
- Exercise: Neural Modeling and Analysis
Chapter 3: Supervised Learning
- Exercise: Supervised Learning
Chapter 4. Reinforcement Learning
- Appendix: Gymnasium
- Exercise: Reinforcement Learning
Chapter 5. Unsupervised Learning
- Exercise: Unsupervised Learning
Chatper 6. Bayesian Approaches
- Appendix: Bayesian Model Fitting by PyStan
- Exercise: Bayesian Approaches
Chapter 7: Deep Learning
- Exercise: Deep Learning
Chapter 8. Multiple Agents
- Exercise: Multiple Agents
Chapter 9. Meta-Learning
- Exercise: Meta-Learning

Binder
Colab

.ipynb

Exercise: Meta-Learning

Exercise: Meta-Learning#

Come up with daily-life examples of “learning to learn” and consider what computational processes may be involved.

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Chapter 9. Meta-Learning

By Kenji Doya

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