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Hands-On Meta Learning with Python. Meta learning using one-shot learning, MAML, Reptile, and Meta-SGD with TensorFlow

Język publikacji: angielskim
Hands-On Meta Learning with Python. Meta learning using one-shot learning, MAML, Reptile, and Meta-SGD with TensorFlow Sudharsan Ravichandiran - okladka książki

Hands-On Meta Learning with Python. Meta learning using one-shot learning, MAML, Reptile, and Meta-SGD with TensorFlow Sudharsan Ravichandiran - okladka książki

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Meta learning is an exciting research trend in machine learning, which enables a model to understand the learning process. Unlike other ML paradigms, with meta learning you can learn from small datasets faster.
Hands-On Meta Learning with Python starts by explaining the fundamentals of meta learning and helps you understand the concept of learning to learn. You will delve into various one-shot learning algorithms, like siamese, prototypical, relation and memory-augmented networks by implementing them in TensorFlow and Keras. As you make your way through the book, you will dive into state-of-the-art meta learning algorithms such as MAML, Reptile, and CAML. You will then explore how to learn quickly with Meta-SGD and discover how you can perform unsupervised learning using meta learning with CACTUs. In the concluding chapters, you will work through recent trends in meta learning such as adversarial meta learning, task agnostic meta learning, and meta imitation learning.
By the end of this book, you will be familiar with state-of-the-art meta learning algorithms and able to enable human-like cognition for your machine learning models.

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O autorze książki

Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.

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