LearnML vs AI Neural

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.

AI Neural Network Primer is an interactive educational app that turns "neural networks" from abstract formulas into something you can play with hands-on. No AI background required, no internet needed — all models run in real time on your device. Just touch, observe, and uncover the secrets of deep learning step by step. From the first handwritten digit to the most cutting-edge large models, the courses take you from beginner to advanced: white-box visualizations let you literally "see" how data flows through every layer of the network, while hands-on training shows you why it works. 12 interactive models plus a live camera turn a textbook into an AI lab you can play with anytime. This app includes 6 fascinating courses: 1. Understanding Neural Networks Through a Single Digit Using handwritten digits as input, watch the entire forward propagation process in a white-box view — from pixels to recognition results. You can even train your first neural network yourself and witness every step as it goes from random guessing to accurate recognition. 2. What Is a Convolutional Neural Network Starting from a sample image, walk through the complete forward inference of a CNN from input to output. Follow the animation step by step to clearly see "convolution → activation → pooling → classification", and understand the core technology behind image recognition. 3. Mastering YOLO Object Detection Use the live camera or local photos to operate the YOLO model yourself and detect objects in the scene in real time. Experience real object detection technology running smoothly before your eyes. 4. Exploring Transformers Dive deep inside the Transformer model and interactively observe how text passes step by step through embedding, self-attention, and stacked Transformer blocks to finally generate coherent responses. The core of modern large language models, seen this clearly for the first time. 5. MoE: Mixture of Experts Explore the "Mixture of Experts" mechanism. Watch as the Router intelligently routes each token to the most suitable expert, and discover the secret behind how mainstream large models scale up and speed up. 6. Multimodal Large Models Experience image-text multimodal large models with SmolVLM: input an image and text at the same time, and observe how visual information merges with text to generate answers. Your gateway to multimodal technology. Why choose it: - White-box visualization: every layer and every step of computation inside the network is shown in real time — no more guessing - Hands-on learning: draw digits, pick images, turn on the camera, train models — learn while you play - Fully offline: pure on-device inference. Download models once, keep your privacy yours — zero privacy risk - Step by step: from CNNs to multimodal large models, 6 progressive courses that complete beginners can follow Whether you're a student getting started with AI, a teacher who needs visual explanations, or simply curious about neural networks — immerse yourself in a world of deep learning you can see and touch.