Lightly Discussions

Lightly helps machine learning teams to build better models through better data. It helps to curate unlabelled data to improve its quality for model training. 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. 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. Manage your dataset. Apply automated labeling. Track different versions, and once your dataset is ready, simply share with labeling with the click of a button. When users leave Lightly reviews, G2 also collects common questions about the day-to-day use of Lightly. These questions are then answered by our community of 850k professionals. Submit your question below and join in on the G2 Discussion.