LearnML
RABBIT HOLE STUDIO LTD
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About this app
Learn how a neural network works by building and training one yourself. LearnML takes you through four steps: Data, Model, Train and Try it. START WITH A WORKING EXAMPLE Make your first prediction with a ready-to-use even-or-odd model. Short explanations show what each step does and what to try next. LEARN THROUGH THREE GUIDED LESSONS • Classify numbers as even or odd. • Predict a temperature from previous values. • Explore image classification with animal photos. The temperature examples are simulated learning data, not a weather forecast service. BUILD AND EXPERIMENT Choose number, vector or image inputs. Edit examples, select the correct answers and build a model from dense, convolution, pooling, activation and dropout layers. Start with a matching model or change its architecture and training settings. TRAIN ON YOUR DEVICE Watch progress and compare training and test metrics. Stop a run when you need to. Try a new number, set of values or photo after training. Predictions can be wrong: use them to explore what the model learned. KEEP YOUR WORK Experiments, examples, trained models and lesson progress are saved locally between launches. Rename and duplicate experiments, keep successful training runs, or export and import an experiment as a JSON file. Interrupted training can be started again from the restored experiment. MADE FOR IPHONE AND IPAD Follow one step at a time on iPhone. Use the sidebar on iPad and view a lesson's explanation beside its practice area when space allows. English and Russian interfaces are included, with support for larger text and improved accessibility controls. No account or cloud training is required. Choose your own photos or use the built-in examples.
What's new
Version 1.2 · Oct 13, 2026
• A clearer Data → Model → Train → Try it workflow and a guided first prediction. • Experiments, examples, trained models and lesson progress now survive app relaunches. • Rename, duplicate, delete, export and import experiments; keep successful training runs. • Updated number, temperature and image lessons with clearer explanations and small practice tasks. • Improved reliability and validation for training and predictions, including image experiments. • An adaptive iPad workspace, improved larger-text and accessibility controls, and a Russian interface.
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