Liner enables users to build and deploy machine learning models without writing code. It simplifies the process of training models for various applications, including image and text classification, object detection, and more, making machine learning accessible to individuals without technical expertise.
Features
- Supports multiple machine learning types: image classification, text classification, audio classification, video classification, object detection, image segmentation, and pose classification
- Automatic model selection and training based on provided data
- Data import and visualization capabilities
- Model export options for integration with various platforms
- Optimized for speed and accuracy, with most models trained within minutes
- No GPU required; models are optimized for CPU training
- Edge-optimized models suitable for mobile and edge devices
Use Cases
- Developing image classification models for identifying objects in photos
- Creating text classification models for sentiment analysis or spam detection
- Building audio classification models for recognizing different sounds or speech patterns
- Implementing object detection models for real-time video analysis
- Designing pose classification models for fitness or rehabilitation applications
Summary
Liner stands out by offering a user-friendly interface that allows users to train and deploy machine learning models across various applications without requiring coding skills. Its optimization for speed and compatibility with both CPU and edge devices make it a versatile tool for rapid machine learning development.
