This repository contains Jupyter notebook implementations of three neural process model variants: Conditional Neural Processes (CNPs), Neural Processes (NPs), and Attentive Neural Processes (ANPs). These are deep learning architectures that combine neural networks with stochastic processes for meta-learning tasks, enabling function approximation from limited context data. The code runs on TensorFlow and can be executed in the browser via Google Colab or locally with Jupyter.