Liner

Liner is a free, no-code machine learning platform that enables users to build, train, and deploy custom ML models within minutes, without requiring any programming skills or deep knowledge of machine learning algorithms. The tool is designed for a broad audience, including business analysts, product managers, educators, researchers, and hobbyists who want to integrate AI capabilities into their projects but lack coding expertise. Liner streamlines the entire machine learning workflow into three straightforward steps: data import, automated training, and model integration. First, users can import their own labeled datasets—commonly in formats like CSV, Excel, or image folders—directly into the Liner interface. The platform also provides pre-labeled sample datasets for common tasks, such as image classification, text categorization, or numeric regression, so beginners can experiment without preparing data from scratch. Once imported, Liner displays a preview of the data, allowing users to inspect features, labels, and distributions. Second, with a single click, Liner initiates an automated training process. The system automatically selects an appropriate machine learning algorithm based on the data type and task (e.g., convolutional neural networks for images, gradient boosting for tabular data, or transformer-based models for text). It handles data preprocessing, feature extraction, model selection, hyperparameter tuning, and cross-validation internally, so users do not need to tweak any settings. Training progress is shown in real time, and users can see metrics like accuracy, loss, precision, recall, or F1 score as the model learns from the provided data. For image tasks, Liner supports common scenarios such as binary classification (e.g., cat vs. dog) or multi-class