Getting-Things-Done-with-Pytorch

Why we included this project

This repo collects Jupyter notebooks that take real PyTorch projects from a blank notebook to a working result, rather than dropping you in the middle of a polished script. You get complete walks through NLP, computer vision, and time series work: building a first neural network, training a BERT sentiment model, and serving it as a FastAPI REST endpoint. Every tutorial ships with a Colab-ready notebook and the matching blog post, so you can read the reasoning, run the cells yourself, and compare outcomes without hopping between docs. It suits developers and small teams who know Python basics and want to see object detection, face detection, or time series anomaly detection applied to their own data.