Lightly membantu pasukan pembelajaran mesin memilih dan mengurus data latihan menggunakan pembelajaran aktif: menapis sampel, menganalisis kualiti/diversiti, dan memantau prestasi model.
Lightly helps machine learning teams to build better models through better data. It allows companies to select the right data for model training by using active learning. Intelligently select the best samples for model training through advanced filtering and active-learning algorithms.
- Balance your class distributions, remove redundancies and dataset bias. Label only the best data for model training until you reach your target accuracy.
- Analyze the quality and diversity of your datasets. Better understand your data with Lightly's holistic views from the big picture down to the smallest nuances of your data. Uncover class distributions, dataset gaps, and representation biases before labeling to save time and money.
- Monitor your model performance in production. Spot outliers and failure cases.
- Select out-of-distribution data directly on the edge or cloud. Send data back for retraining and updating the model.
- Manage your dataset. Track different versions, and once your dataset is ready, simply share with labeling with the click of a button.
That's Lightly: The end-to-end active learning
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