eat Pytorch in 20 days

Eat PyTorch in 20 Days is an open-source educational project that provides a structured introduction to deep learning development with PyTorch. Designed for learners with basic machine learning experience, it organizes tutorials into progressive lessons covering essential concepts and practical workflows. The material explains tensor operations, automatic differentiation, neural network components, and model construction. It demonstrates how to prepare datasets, configure loss functions, manage optimizers, and train models using different approaches. The tutorials also cover GPU acceleration, TensorBoard visualization, and techniques for evaluating model performance. Additional examples explore recommendation systems, advertising algorithms, and architectures such as DeepFM and FiBiNET. Interactive Jupyter notebooks provide reusable code for experimentation and practical development.