The data flywheel: Activeloop and manot.ai for evaluating detections and finding new data PART 3

A data flywheel is a self-sustaining system where the more data you collect, the more value you generate from each sample. It is important because it enables organizations to continuously improve their machine learning models by providing a constant stream of high-quality data.

Activeloop and manot.ai are tools that can help create a data flywheel by providing efficient data management and data filtering. Activeloop enables scalable data management, while manot.ai provides intelligent filtering algorithms that learns what data your model needs to improve.

Annotation can be a costly process, both in terms of time and resources. Not all images are equally valuable, and it is important to prioritize annotation of images that have the most impact on the model's performance.

This is the third video in the Activeloop series:

Data exploration and versioning with Activeloop and Deep Lake for Machine Learning PART 1

Data exploration and versioning with Activeloop and Deep Lake for Machine Learning PART 2

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