I built a visual drag-and-drop ML trainer (no code required). Free & open source.

For those who are tired of writing the same ML boilerplate every single time or to beginners who don't have coding experience. MLForge is an app that lets you visually craft a machine learning pipeline. You build your pipeline like a node graph across three tabs: Data Prep - drag in a dataset (MNIST, CIFAR10, etc), chain transforms, end with a DataLoader. Add a second chain with a val DataLoader for proper validation splits. Model - connect layers visually. Input -> Linear -> ReLU -> Output. A few things that make this less painful than it sounds: Drop in a MNIST (or any dataset) node and the Input shape auto-fills to 1, 28, 28 Connect layers and in_channels / in_features propagate automatically After a Flatten, the next Linear's in_features is calculated from the conv stack above it, so no more manually doing that math Robust error checking system that tries its best to prevent shape errors. Training - Drop in your model and data node, wire them to the Loss and Optimizer node, press R