ELTE PPK vs LearnML

English: UNI@HAND – A smartphone app designed for the students of the ELTE Faculty of Education and Psychology. This app has all you need as a student here in our faculty, just as informations with your educational affairs, complete list of contacts to your teachers, and even well-detailed floorplans of our buildings. If you are not familiar with the facilities of the streets around, we have some advices on the best spots to have breakfast, a cup of coffee in the afternoon, or some beer at the evening with your friends. Magyar: UNI@HAND – Alkalmazás az ELTE PPK hallgatóiért. Az UNI@HAND egy helyre gyűjti a hallgatói élethez nélkülözhetetlen összes információt, legyen szó tanulmányi ügyekről, oktatók elérhetőségeiről vagy a kar épületeinek alaprajzáról. Ha új vagy a környéken, biztos hasznosnak fogod találni az egyetem környékén található étkezdék, kávézók, szórakozóhelyek listáját, amiket hallgatótársaink véleménye alapján állítottunk össze. Az alkalmazás folyamatosan fejlődik, szeretettel várjuk javaslataidat, ötleteidet.

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.