Automate Variable Selection for Research on Big Datasets (Open-Source)
A tool to automate variable selection for research on large datasets. The provided example is on the variable dictionary of the UK Biobank Dataset. It utilises the GPT-4 API to include/exclude and categorise the 8000+ variables in the UK Biobank. It also provides a concise explanation for each varia
Automate Variable Selection for Research on Big Datasets (Open-Source) launched on February 1, 2024 with 8 votes, #1,589 of 3,962 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 2 years on.
What it does
A tool to automate variable selection for research on large datasets. The provided example is on the variable dictionary of the UK Biobank Dataset. It utilises the GPT-4 API to include/exclude and categorise the 8000+ variables in the UK Biobank. It also provides a concise explanation for each variable regarding the inclusion/exclusion decision. - MalikHarrisAhm/Big-Data-Variable-Selector-Tool
Does a similar job
all alternatives →
AutoML Python Package for Tabular Data with Automatic Documentation2022 · github.com · ▲67Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation - mljar/mljar-supervised
Viable 2.0 - Generative Analysis2023 · askviable.com · ▲193AI analysis for people with too much data & not enough time
A Python tool for text-based AI training and generation using GPT-22020 · github.com · ▲174A robust Python tool for text-based AI training and generation using GPT-2. - minimaxir/aitextgen
Fully client-side GPT2 prediction visualizer2023 · perplexity.vercel.app · ▲153Hi HN! I've found this visualization tool immensely helpful over the years for getting an intuition for how an LLM "sees" some piece of text, and with a bit of elbow grease decided to move all compute to client side so I could make it publicly available. I've found it particularly useful for - Understanding exactly how repetition and patterns affect a small LM's ability to predict correctly - Understanding different tokenization patterns and how it affects model output - Getting a general sense of how "hard" different prediction tasks are for GPT-style models Known problems (that I probably…
Autolabel, a Python library to label and enrich text data with LLMs2023 · github.com · ▲153Hi HN! I'm excited to share Autolabel, an open-source Python library to label and enrich text datasets with any Large Language Model (LLM) of your choice. We built Autolabel because access to clean, labeled data is a huge bottleneck for most ML/data science teams. The most capable LLMs are able to label data with high accuracy, and at a fraction of the cost and time compared to manual labeling. With Autolabel, you can leverage LLMs to label any text dataset with <5 lines of code. We’re eager for your feedback!
AutoAI – A framework to find the best performing AI/ML model2021 · github.com · ▲41Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation. - blobcity/autoai
More ai this month
the category →
Paintings by AI models: programs run through a simulation of oil paint.
AI · 22d ago · stillwet.art
FastRouter.ai▲364Route requests to the right LLM for cost, latency & quality
AI · 23d ago · fastrouter.ai
Source: Show HN post ↗
Launched alongside, February 2024
the whole month →
MarketingIdeas.com▲1,230Never run out of marketing ideas ever again
Growth · 2024 · marketingideas.com
