This repository provides companion code for the book Hands-On Meta Learning with Python. It contains Jupyter notebooks implementing various meta-learning algorithms including MAML, Reptile, Meta-SGD, siamese networks, prototypical networks, relation networks, and memory-augmented networks using TensorFlow and Keras. The material covers one-shot learning, few-shot learning, zero-shot learning, and related concepts in learning to learn.