本教程旨在为完全没有编程经验的初学者提供一个从头开始学习使用Python构建神经网络的全面指南。通过逐步讲解和实践项目，帮助读者掌握必备技能并理解核心概念。
Implementing a Neural Network from Scratch--An Introduction
This article provides an introduction to building a neural network using Python, starting with the basics and gradually moving towards more complex concepts. It covers fundamental topics such as forward propagation, backpropagation, activation functions, loss functions, and optimization algorithms. The goal is to give readers a comprehensive understanding of how neural networks work under the hood by implementing one from scratch without relying on high-level libraries like TensorFlow or PyTorch.
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