Building Image Classification Web Apps with Teachable Machine

Machine learning does not require complex mathematics or deep data science backgrounds to build engaging, interactive web applications. This text-based course guides you through creating functional image recognition tools, from data gathering to a live browser-based app. You will understand the core principles of computer vision, prepare clean training datasets, and train custom classification models using Teachable Machine. You will then export your model and integrate it into a responsive web interface using HTML, CSS, and modern JavaScript, allowing users to upload images and receive similarity predictions in real time. What you'll learn: - Understand fundamental concepts of machine learning, classification, and computer vision - Collect, organize, and preprocess image datasets for balanced model training - Train, test, and fine-tune image recognition models using Teachable Machine - Export trained models and integrate inference logic into modern JavaScript applications - Structure clean HTML and CSS to create an intuitive upload and prediction interface - Handle client-side image processing, user privacy, and basic deployment workflows The course begins with foundational terminology and artificial intelligence principles before guiding you through data preparation, model training, and step-by-step web integration. This course is designed for beginners, aspiring web developers, and creators who want to build practical AI-powered web applications without prior data science experience. Start reading today and bring your first machine learning web project to life.