Interactively explore unstructured datasets from your dataframe
Hey HN, We built a library to interactively explore unstructured datasets directly from a dataframe: https://github.com/Renumics/spotlight Some background: We have worked on different ML solutions over the years, mainly in the industrial AI space. A crucial step for us is always to inspect and explore the data interactively with the team and the customer. This is true throughout the dev process: During EDA, model debugging, model comparison and monitoring. We have tried many different options for visualizing unstructured datasets in the past: Notebooks, dash apps, custom…
Interactively explore unstructured datasets from your dataframe launched on September 4, 2023 with 6 votes, #1,645 of 4,228 launches that month and more than 50% of that year's launches. The site was still online in September 2026, 3 years on.
What it does
Interactively explore unstructured datasets from your dataframe. - Renumics/spotlight
In the maker’s words, at launch
Hey HN, We built a library to interactively explore unstructured datasets directly from a dataframe: https://github.com/Renumics/spotlight Some background: We have worked on different ML solutions over the years, mainly in the industrial AI space. A crucial step for us is always to inspect and…
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- RSRenumics Spotlight – Multimodal exploration tool for your datasets2023 · renumics.com · ▲6
Hey HN! We just released the open-source version of Renumics Spotlight, a data exploration and analysis tool for multimodal datasets. Spotlight integrates seamlessly with pandas and supports rich data types like images, videos, and meshes. You can load anything that fits in a DataFrame and view it through a customizable GUI featuring multiple interactive widgets: a data table, similarity map, histograms, scatter plots, and more. In the past, we have used Spotlight for exploratory data analysis and tackling various model and data-related problems in our machine learning projects. What are…
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Source: Show HN post ↗ · launch text quoted in part
