Alternatives
Products that do what Renumics Spotlight – Multimodal exploration tool for your datasets does
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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Hi HN! I’m Alex from Parabola (https://parabola.io). Parabola is a visual programming tool for creating functional data flows that everyone can use. It’s entirely drag-and-drop, handles data sizes much larger than a traditional spreadsheet, calculates everything live, and can run your flows on a schedule of your choosing. I used to work in strategy consulting, doing data analytics for SMBs and Fortune 500 companies. The amount of time wasted on menial tasks was astounding. Things like cleaning data, generating custom reports, creating human workflows to solve shortcomings in third…
2018 · parabola.io
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Dear HN, I am Riwaj, the cofounder of dstack.ai (https://github.com/dstackai). A few months ago, we built an online service that allows users to publish data visualizations from Python or R. The idea was to build a tool that did not require additional programming or front-end development for publishing data visualizations. Such a code can be invoked from either Jupyter notebook, RMarkdown, Python, or R scripts. Once the data is pushed, it can be accessed via a browser. Open-sourcing dstack: During our customer discovery phase, we realized that dstack.ai should integrate a lot…
2020
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2017 · dataprism.co
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2018 · medium.com
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Hey HN, when building ML systems for industrial AI, we have learned that data inspection is critical during the ML development process. We are also big fans of the Hugging Face ecosystem. That is why we built an integration to our data exploration tool Spotlight that allows you to interactively explore Hugging Face datasets with one line of code. Spotlight lets you leverage model results such as predictions and embeddings to gain a deeper understanding in data segments and model failure modes. Currently, many many NLP, CV, Audio and multimodal datasets are supported both locally and on the…
2023 · huggingface.co
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2019 · bamboolib.com
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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…
2023 · github.com
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2020 · github.com
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Hi HN! I am Maria, solo founder of DataQA (https://dataqa.ai/), a tool to search and label documents for various NLP tasks (e.g. entity extraction, entity linking, etc). I have worked as a data scientist and ML engineer for the better part of a decade, and over that time have specialised mainly in applications involving natural language processing (NLP). One of the key questions I have always had at the back of my mind is whether my time was well spent. Whenever I spent more time on feature engineering or trying different models, I always wondered whether I would get better…
2021
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2016 · datasets.co
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Hey HN, Data quality matters more than ever. Our world increasingly relies on AI and proprietary datasets to fine-tune models. But as many of us know, garbage in often results in garbage out. Bad data can cost millions, especially when it informs important decisions like public health policy or interest rate hedging. Today’s data engineers need a flexible, secure, and performant data quality toolkit designed for the modern workflow. But current solutions were built a decade ago and don't support big data technologies, such as Spark. This is why we're building Spotlight - the data quality…
2023 · spotlight.dev
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Visions is a python library for working with user defined data type systems. Out of the box, it provides type inference and automated data cleaning of sequence data with backend specific implementations for pandas, spark, python, and numpy. We often use it as a first pass cleaning step when working with tabular data and to simplify the backend logic of both pandas-profiling[1] and our tabular data compression library compressio[2]. Because data types are user defined, we can build user customizable libraries based around types without adding code complexity. In the case of compressio that…
2022 · github.com
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2021 · github.com
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Hi HN! I am an undergrad student trying to build interesting things with AI. Recently, I was looking for a dataset I could use for a new project. I realized that it is really frustrating to go through all the government websites (with terrible UX) just to find some usable dataset. I set out to build a GitHub for datasets, named DataHub. Right now, we have more than 1000 datasets from Montréal and New York City, with more cities coming soon (and possible government agencies). All of this is wrapped into a powerful search. It's a breeze to find a dataset to work on. I'd be interested to know…
2017
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Hi everyone, I’d like to introduce Amphi, a free and source-available visual data transformation tool. Amphi is a low-code tool designed for data preparation, manipulation and ETL tasks, whether you're working with files or databases, and it supports a wide range of data transformation operations. The main difference from tools like Alteryx or Knime is that Amphi is based on Python and generates native Python code (pandas and DuckDB) that you can export and run anywhere. You also have the flexibility to use any Python libraries and integrate custom code directly into your pipeline. It is…
2024 · github.com
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Hey everyone! I am excited to share updates on four of my & my teams' open-source projects that take large-scale search systems to the next level: USearch, UForm, UCall, and StringZilla. These projects are designed to work seamlessly together, end-to-end—covering everything from indexing and AI to storage and networking. And yeah, they're optimized for x86 AVX2/512 and Arm NEON/SVE hardware. USearch [1]: Think of it as Meta FAISS on steroids. It's now quicker, supports clustering of any granularity, and offers multi-index lookups. Plus, it's got more native bindings than probably…
2023 · usearch-images.com
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Hey all! I wrote Explorer[1] a good few years ago now with the dream of fast dataframes with a dplyr-like API in a really powerful, ergonomic language (Elixir). It's proved pretty successful. Explorer is used in production at my company, and it's my go-to for quick data analysis. But maintaining it became a true albatross. Polars is an amazing project, but the development process is fast and a lot is very focused on the Python lib. We found that trying to maintain Explorer against Polars was a maintenance nightmare and eventually hit points where we had to give up features and found it…
Mar 2026 · github.com
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I wanted to share something I've been working on recently: Statum, a handy web analytics tool. https://github.com/extractumio/statum The journey began when I found myself frequently needing simple web analytics for my projects. I tried Google Analytics, especially GA4, and realized it was quite complex and, at times, not very accurate, especially when I wanted to view stats for the current day or recent hours. Then I tested a few fancy startup solution but ended up with way too expensive plans the expect me to subscribe (I'm not that rich to pay $99/month for every…
2023 · github.com
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2019 · github.com
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