Our meta learner can be any meta learning algorithm, say MAML, Meta-SGD, or Reptile, parameterized by 
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- Title Page
- Copyright and Credits
- Dedication
- About Packt
- Contributors
- Preface
- Introduction to Meta Learning
- Face and Audio Recognition Using Siamese Networks
- Prototypical Networks and Their Variants
- Relation and Matching Networks Using TensorFlow
- Memory-Augmented Neural Networks
- MAML and Its Variants
- Meta-SGD and Reptile
- Gradient Agreement as an Optimization Objective
- Recent Advancements and Next Steps
- Assessments
- Chapter 1: Introduction to Meta Learning
- Chapter 2: Face and Audio Recognition Using Siamese Networks
- Chapter 3: Prototypical Networks and Their Variants
- Chapter 4: Relation and Matching Networks Using TensorFlow
- Chapter 5: Memory-Augmented Neural Networks
- Chapter 6: MAML and Its Variants
- Chapter 7: Meta-SGD and Reptile Algorithms
- Chapter 8: Gradient Agreement as an Optimization Objective
- Chapter 9: Recent Advancements and Next Steps
- Other Books You May Enjoy
Meta learner
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