DataGradients enables data scientists to avoid pitfalls and save precious development time with better visibility into their data, streamlining the model design and training processes
TEL AVIV, Israel, July 12, 2023 — Deci, the deep learning company harnessing AI to build AI, today announced the release of DataGradients, a free, open-source tool for profiling computer vision datasets and distilling critical insights.
In the realm of computer vision, an AI model’s power is inherently linked to the quality of the data used for training. Identifying issues in the dataset is paramount, as it not only helps practitioners steer clear of training roadblocks but also sheds light on a model’s potential underperformance. A good read on a dataset’s attributes can help streamline decisions like the appropriate model choice, the best loss function, and the ideal optimization method.
“DataGradients empowers data scientists to streamline their model development and training process, with crystal-clear visibility into their data. With DataGradients, we’ve made it that much easier to extract actionable insights from one’s datasets,” said Yonatan Geifman, CEO and co-founder of Deci. “DataGradients marks our third tool released as open source to the benefit of the wider AI community, following our launch of SuperGradients, our free, open-source training library for PyTorch-based deep learning models, and YOLO-NAS, our groundbreaking object detection foundation model.”
Using DataGradients, data scientists can easily analyze the health of their data with one line of code, swiftly identifying problems such as corrupted data, distributional shifts between train and test sets, duplicate annotations, among many others. Users then receive actionable insights on how to proactively mitigate such issues to streamline their model design and training processes, thereby ensuring optimal performance and reliable results.
If you would like to profile your data or start training your models, visit DataGradients on Deci’s GitHub repository.
This announcement was originally published on Cision PRWeb.
