Train a Convolutional Neural Network from Scratch: PyTorch, Next.js, React, Tailwind, Python (2025)

A comprehensive tutorial covering the complete process of building a convolutional neural network from scratch using PyTorch to classify audio files. The guide starts with neural network fundamentals including neurons, activation functions, and training concepts like forward pass, backpropagation, and loss optimization. It then dives deep into CNN theory, explaining kernels, feature maps, spatial information preservation, and how CNNs extract hierarchical features from images. The practical implementation includes converting audio to spectrograms, training on serverless GPUs with Modal, achieving 83% accuracy, and building a Next.js frontend to visualize the model's convolutional layer outputs and feature extraction process.