ML_Engineering vs AI Neural

Become a machine learning engineer—starting exactly where you are. ML_Engineering is a complete interactive learning environment for iPhone, iPad, and Mac. Begin with basic arithmetic, examples, features, labels, and your first prediction baseline. Progress through Python, NumPy, pandas, statistics, feature engineering, classical machine learning, deep learning, computer vision, NLP, forecasting, recommendations, model serving, MLOps, monitoring, responsible ML, distributed training, LLM systems, and principal-level ML architecture. LEARN BY DOING • 40 structured courses from beginner to advanced • 400 substantive interactive lessons • 140 editable, syntax-highlighted code labs • 100 quizzes with validation and explanations • 80 architecture decisions based on production trade-offs • 80 guided concept exercises • Progressive hints that help without giving away the answer BUILD A SERIOUS ML PORTFOLIO Complete 40 practical projects: 12 Beginner, 14 Intermediate, and 14 Advanced. Build baselines, classifiers, forecasts, recommenders, vision and language models, feature stores, inference services, experiment systems, model registries, drift monitors, ML delivery pipelines, distributed training, LLM evaluation, governance controls, and a principal ML platform design. Every project includes an editable workspace, four milestones, checks, and outcomes you can explain in an interview. YOUR PRIVATE ML ENGINEERING TUTOR Ask from any lesson or project. Tutor Core can begin with basic arithmetic, define every new term, explain how models learn, diagnose code and architecture, and continue until the idea clicks. Offline Core is included and never sends questions anywhere. Compatible devices can add private Apple on-device generation. API, Ollama, and LM Studio connections are always optional. WATCH YOUR ML SYSTEM TAKE SHAPE Every completed lesson, course, and milestone advances a living ML-system construction scene—from problem framing and a baseline through features, training, serving, monitoring, and production guardrails. DESIGNED FOR SERIOUS PROGRESS Earn XP, build streaks, bookmark material, track role readiness, choose daily goals, switch between light and dark interfaces, and move naturally among iPhone, iPad, and Mac. FREEMIUM AND PRO Explore the first module of every course for free, keep your learning progress, and upgrade only when you are ready. ML_Engineering Pro unlocks the complete curriculum, every lab and portfolio project, and contextual Tutor access across iPhone, iPad, and Mac. Choose a monthly plan with a 14-day free introductory trial or an annual plan with a 7-day free introductory trial, when eligible. Prices are shown before purchase. Payment is charged to your Apple Account after confirmation. Subscriptions renew automatically unless cancelled at least 24 hours before the end of the current period. Restore purchases or manage your subscription directly from the app. Terms of Use: https://www.apple.com/legal/internet-services/itunes/dev/stdeula/ Privacy Policy: https://github.com/lukekevinmclaughlin-oss/ML_Engineering/blob/main/PRIVACY.md

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.