Hi, I would like to have some images of different network topologies varying from simple buss topologies to complex actual networks. Anyone know about a suitable dataset containing such diagrams?
This is for my project where I will be testing LLMs with vision capabilities for there ability to spot faulty network topologies, perhaps the topologi is dependent on one device not going down, or a server should be moved to a DMZ. Something like that. appreciate all feedback.

Interesting challenge dataset

Hi all! i’m looking for a dataset with companies and employees data, i’d like to use it in a small startup, offering such data to people who would like to contact those companies and employees. Apollo and all the alternatives does not let you “sell” their info.. do you know any provider that lets you resale? Thank you

Does anybody know where I could find a Aerial ndvi dataset of crops or rgb and nir dataset of crops/Leaves.

Disclosure: this is a self promotion post.

I’ve been noticing that a lot of health and habit apps require accounts and store personal data in the cloud — even for something as simple as tracking medication.

That feels unnecessary, especially for something so sensitive.

So I built a medication tracker that works completely offline:

no login

no data collection

everything stays on your phone

https://play.google.com/store/apps/details?id=com.vnytalab.carebell

I’m trying to keep it as simple and private as possible.

Would love some honest feedback on this approach — do you actually care about privacy in apps like this, or is convenience more important for you?

Hey guys, I’m Adipooj, and over the course of a few months, my buddy and I built a synthetic data generator, that generates customisable datasets for credit card transactions with fraud injected in them, for use in ML, AI Training, Validation, and most importantly Model Testing!

If this is something that interests you, shoot me a DM, I’d love to send you a sample and get your thoughts on it!

I need a dataset of monthly prices of crude oil/LNG/diesel globally from 2018 to 2026. Something similiar to this https://www.iea.org/data-and-statistics/data-product/energy-prices#crude-oil-import-costs-and-index-by-country which isn’t paywalled. I am a student so I have access to some sites through my email if that helps.

I’m looking for US healthcare contact datasets that cover CXOs and IT decision makers. Specifically, I’m interested in records that may include roles like CIO, CTO, VP of IT, Director of IT, CMIO, CEO, COO, and other relevant decision-makers across hospitals, health systems, clinics, medical groups, and related healthcare organizations.

If you have something relevant, pls reply or DM with the details like coverage, last updated date, asking price, etc.

Initial release of the African Countries Indicators dataset v1.0.0

https://zenodo.org/records/19647480

• Initial release of the African Countries Indicators dataset v1.0.0 54 sovereign African nations
• 10 variables: geographic, demographic, and administrative indicators
• Formats: CSV and XLSX
• Sources: World Bank, World Atlas, ISO, Google Developers
• African Countries Indicators DataSet

Wondering if someone has a few years’ worth of government emails, the kind that are sent out to subscribers, sub-agencies, etc. Example: the regular emails sent out by the DOJ, HHS, etc.

I’ve been building a system that generates fully instrumented agentic SDLC traces, and I’m looking for a few serious folks to evaluate it and share results.

Not selling anything here — I’m interested in whether this actually moves model behavior in practice.

What the dataset includes (per “packet”):

• Full agent execution trace (JSONL audit log)
• Inline action protocol (custom XML-style commands, also normalized to R1 <|TOOL_CALL|> format)
• Reinference loops (action → result → next action preserved)
• Complete project source code
• Full file evolution history (create/edit/delete with snapshots)
• SQLite DB with structured tables (runs, tool calls, plans, etc.)
• Precomputed embeddings (4096d, PII-sanitized)
• Viewer + ETL tooling to load into your own stack
• All generated with OSS models w/ verified licenses

Key difference vs typical datasets:
This isn’t just prompts → outputs. It’s:

Each project can be iterated:

• v1: initial build
• v2: bug fixes
• v3: polish
• v4: feature expansion
• v5: integrations

So you get longitudinal behavior, not isolated samples.

What I’m looking for:

• People fine-tuning models (1B–120B, LoRA or full SFT)
• Agent / tool-use training experiments
• Anyone doing evals on:
  • tool use correctness
  • code editing / repair
  • multi-step task completion

In exchange:
I’ll provide a dataset bundle (or multiple), and I’m asking for:

• honest feedback
• any measurable results (even rough)
• what worked / didn’t
• where the data helped or failed

No obligation to share publicly if you don’t want to — even private feedback is useful.

A few things I’m specifically curious about:

• How much data (tokens) is needed to see behavioral shifts
• Whether iteration sequences (build → fix → extend) actually help
• Whether models learn better recovery behavior from failed traces
• Impact on tool-call correctness / formatting

If you’re interested, comment or DM with:

• what models you’re working with
• what you’d want to test

Happy to tailor a dataset slice to your use case.

Would also appreciate any critique on the structure itself — trying to figure out if this is genuinely useful or just interesting.

I’m a final-year Software Engineering student working on my FYP.

My proposed project is an AI system for detecting abnormalities in brain CT scans For ( (Normal, hemorrhage, stroke, edema)

I need some guidance from people in the medical/AI/research field:

• Where can I get real CT brain scan data sets
• Are there any public datasets or institutions that provide this kind of medical imaging data?
• What are the main challenges I should expect when working with this kind of data?

If anyone has experience with medical AI, radiology datasets, or hospital collaborations, your advice would really help me shape my project in the right direction.

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Guys please help me out. I need sources where i can find medical dataset for the disease Creutzfeldt-Jakob.

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How to extract Inc 5000 2025 fastest growing list for free?

I have been trying to find it .. but seems like almost impossible. If anyone can help then that would be of great help. Thanks!

I spent six months cataloging every construction software tool I could find and just open-sourced the aggregate data.

15 categories, 570 tools, columns for pricing model, mobile coverage, and company size targeting.

MIT license on the data, CC-BY on the analysis.

Some findings:

• 55% of vendors hide their pricing behind a sales call. In Safety & Compliance the number climbs to 81%.
• Only 45% have a mobile app. 83% of bidding tools are desktop-only.
• 9% target solo operators.
• 3 categories have zero options for one-person operations: Document Management, Field Management, and Safety & Compliance.

Happy to answer questions about methodology.

Disclosure: I also run ConTechFinder, the directory the data comes from.

I’m a computer science student working on an independent research project studying how large language models respond to different prompt framings.

I’m building a dataset of annotated model responses and looking for a few contributors to help with labeling.

Task:

• Read short LLM responses (2–5 lines)
• Assign simple labels (agreement, reasoning quality, etc.)
• No writing required, just structured selection

Setup:

• Work is organized in small batches (50–100 samples at a time)
• Clear rubric and examples provided
• Focus is on consistency and quality

Contribution options:

• You can contribute as a research collaborator and be acknowledged as an annotator in the paper
• Alternatively, if you prefer not to be credited, a small payment per batch can be arranged

If you’re interested, comment and I’ll share a sample + details.

After a year of scraping + PDF parsing, I put together a fairly complete vehicle specs dataset. Sharing a free sample in case anyone here can use it for their work.

– 47,344 cars (108 brands, 1898–2026)

– 5,492 trucks (146 brands, 1960–2024, GVW/GCW, Euro III–VI, axle configs)

– 1,858 motorcycles (171 brands, 1902–2023, suspension/brake/ABS details)

– 40–50 spec fields per vehicle (engine, performance, dimensions,

features/equipment, fuel consumption, CO2, price when available)

– CSV + SQL + JSON formats

**Free sample** (100 cars + 50 trucks + 50 motos, real data, all columns):

https://api.carsdataset.com – click the green “Get Free Sample” button

There’s also a live search/filter demo on the same page if you want to poke around before downloading.

Paid full datasets start at $299 (motorcycles only) up to $999 (complete bundle), quarterly updates included.

**r/datasets community:** use code `REDDIT20` at checkout for 20% off (or DM me and I’ll send a code directly).

If anyone’s interested in a **resellable license** to redistribute within your own product (non exclusive), DM me – happy to chat about scope and pricing.

Questions or data-quality complaints very welcome – I’d rather fix the data than pretend it’s perfect.

as the caption reveals, i am in dire need of statistics from 2014-2025 on the confirmed dengue disease cases… please help if you have statista premium, thank you!!!!

tl;dr: did lots of physics and feature extraction on benchmark audio deepfake datasets. Data shows thousands to tens of thousands of clips with incorrect or unreported audio compression reported as uncomopressed or ‘clean’ bonifide baselines.

So I ran a massive feature extraction on 20ish industry standard audio deepfake datasets. One of the more interesting findings was that for a bunch of very common sets like ASVspoof 2021, thousands to tens of thousands of files in their bonifide baseline sets do not match the provided metadata. Wide band audio actually heavily compressed to narrowband, audio listed as uncompressed or no codec applied but looks in the data like it came out a cheap cellphone.

I am not sure what to do this info :p would you guys message the dataset authors and suggest a correction to the data? It makes the results of hundreds of papers written under the assumption they were training on propperly anotated data suddently… questionable.

Or am I just full of myself and this kind of undisclosed ‘muddy’ data is fine because ‘AI’

What would you guys do? file it under cool story bro?

i have applied for drugbank data but its been 2 days since their last follow up. Do they mail you if you get access or just it shows uo on the website or did i get ghosted (again 😿)