Hi everyone,

I’m currently working on a business analytics project as part of my academic work at IIT Madras, and I’m seeking access to Point of Sale (POS) data or any related sales/transactional datasets from any business.

Purpose: The data will be used strictly for educational and analytical purposes to explore trends, build predictive models, and derive business insights.

What I’m looking for:

->POS data (product ID, timestamp, quantity, price, etc.)

->Inventory or stock movement records

->Sales by region, time, or category

If you or your organization is willing to help, or if you can point me in the right direction, I’d be incredibly grateful! I’m also open to signing NDAs or any data use agreements as needed.

Any suggestions are also welcomed
Thank You

Hello everyone,

I’m a third-year undergrad student pursuing a degree in Artificial Intelligence and Machine Learning. For my Deep Learning course project, I’m planning to build a model that detects plastic litter both on the ground and in water.

I’m specifically looking for dataset suggestions — preferably satellite or aerial imagery datasets — that could help with training and testing such a model.

If you know of any publicly available datasets, research projects, or organizations that might share relevant data, I’d greatly appreciate your recommendations.

Thanks in advance!

Hello, I am building a chord sound classifier for my system. I badly need dataset for the following chords A, Cm, D, E, Fm, and Gm. Do you guys know where to find dataset for these chords?

Hey everyone,

I put together an API to make it easier to get historical OHLCV stock prices and full financial statements (income, balance sheet, cash flow) without scraping or manual downloads.

The API:

• Returns quarterly reports in JSON format
• Provides complete price history for any US stock
• Is accessible via RapidAPI for easy integration

Could you give me some feedback on:

• Any missing data fields
• How easy it is to integrate into Python/JS workflows
• Other endpoints you’d want added

Here is the link : https://rapidapi.com/vincentbourgeois33/api/macrotrends-finance1

Thanks for checking it out!

Hey everyone,
I’m learning data science and want to build my skills by working on real-world data. If you have any messy datasets (CSV, Excel, Google Sheets) that need:

• Cleaning (removing duplicates, handling missing values, etc.)
• Structuring
• Basic analysis or summary
• Visualizations (charts, graphs)

…I’d be happy to do it completely free — no catch.

You get clean data and maybe some cool insights. I get practice and accountability.
Drop me a message or comment below if you’re interested — I’ll handle only a couple of small projects each week to give proper focus.

Thanks!

Hello, I need a dataset of active ingredient synonyms for a project. Can you help?

Hi everyone!
I’m working on a final year project related to sentiment analysis on students, aiming to explore aspects like mental health, teacher behavior, course feedback, class schedules, and academic stress.

I’m looking for a dataset that contains:

• Student responses or posts (can be survey-based, forum discussions, or open-ended feedback)
• Labeled sentiments (positive/neutral/negative) or at least raw text suitable for labeling
• Data like year of study, age range, CGPA, course/subject, etc.

Does anyone know of such a dataset or where I might find something similar (publicly available or open for research use)? Any help or direction is greatly appreciated!

Thanks in advance!

for eg , let say Fusariosis (Fusarium infections) or Candida auris Infection , i wanted to train my model on these diseases for a research paper but no good dataset till now , if anyone can help me thanks
if not , then i will just increase the saturation , rotate them , add noise and do stuff like that to train

I compiled a clean, ready-to-use dataset of 50+ leads for Facebook ad targeting. I built it because I couldn’t find one that was up-to-date. Here’s a sample: [Google Drive Link]. Let me know if you find it useful. Feedback is most welcome.

I swear if I see one more portfolio project analyzing Titanic survival rates, I’m going to start rooting for the iceberg.

In actual work, 80% of the job is cleaning messy, inconsistent, incomplete data. But every public dataset I find seems to be already scrubbed within an inch of its life. Missing values? Weird formats? Duplicate entries?

I want datasets that force me to:
– Untangle inconsistent date formats
– Deal with text fields full of typos
– Handle missing data in a way that actually matters for the outcome
– Merge disparate sources that almost match but not quite

My problem is, most companies won’t share their raw internal data for obvious reasons, scraping can get into legal gray areas, and public APIs are often rate-limited or return squeaky clean data.

The difficulty of finding data sources is comparable to that of interpreting the data. I’ve been using beyz to practice explaining my data cleaning and decision, but it’s not as compelling without a genuinely messy dataset to showcase.

So where are you all finding realistic, sector-specific, gloriously imperfect datasets? Bonus points if they reflect actual business problems and can be tackled in under a few weeks.

I’m doing a history project on British cars, and I need datasets regarding car sales in Britain going back to at least the 50s, on cars like the Mini, Rolls Royces and Aston Martins. I’ve poked around a bit already, but I can’t find anything that goes back far enough. I want to be able to reference the data sets to see how various forms of advertising (like TV commercials or celebrity endorsement) affected car sales. Would love some help putting all this together!

So i have to make a VQG model that takes image containing geometrical shapes can be multiple and to generate questions like how many type of shapes are there, which is the biggest shape, what color is the square of etc So i have the images now the questions are left i was thinking of annotating the images like types of shapes, color,size etc and use them in some scripts for question like What is (shape_name) color etc So what are your suggestion what to annotate or how to make questions? Thanks

I’m working on a project that requires a dataset containing body images paired with accurate body fat percentage measurements.

I’ve found several DEXA scan datasets, but they only include anthropometric data and no images. I’ve also scraped a number of publicly available images and estimated body fat visually, but I’m looking for a more accurate dataset.

If anyone can recommend an existing dataset or suggest ways to acquire such data, I’d really appreciate it.

I spent years listening to every song to ever get to number one on the Billboard Hot 100. Along the way, I built a massive dataset about every song. I turned that listening journey into a data-driven history of popular music that will be out soon, but I’m hoping that people can use the data in novel ways!

Dataset Explorer is now LIVE, and will stay free forever.

Finding the right dataset shouldn’t be this painful.

There are millions of quality datasets on Kaggle, data.gov, and elsewhere – but actually locating the one you need is still like hunting for a needle in a haystack.

From seasonality trends, weather data, holiday calendars, and currency rates to political datasets, tech layoffs, and geo info – the right dataset is out there.

That’s why we created dataset-explorer. Just describe what you want to analyze, and it uses Perplexity, scraping (Firecrawl), and other sources to bring relevant datasets.

Quick example: I analyzed tech layoffs from 2020–2025 and found:

📊 2023 was the worst year — 264K layoffs 🏢 Post-IPO companies made 58% of the cuts 💻 Hardware firms were hit hardest — Intel topping the list 📅 Jan 2023 = worst month ever — 89K people lost jobs in 30 days

Once you find your dataset, you can run a full analysis for free on Hunch, an AI data analytics platform.

Dataset Explorer – https://hunch.dev/data-explorer Demo – https://screen.studio/share/bLnYXAvZ

Give it a try and let us know what you think.

Check out my project i think it’s neat.

It has a main focus on SISR datasets.

We are releasing WildChat-4.8M, a dataset of 4.8 million real user-chatbot conversations collected from our public chatbots

• Total collected: 4,804,190 conversations from Apr 9, 2023 to Jul 31, 2025.
• After removing conversations flagged with “sexual/minors” by OpenAI Moderations, 4,743,336 conversations remain.
• From this, the non-toxic public release contains 3,199,860 conversations (all toxic conversations removed from this version).
• The remaining 1,543,476 toxic conversations are available in a gated full version for approved research use cases.

Why we built this dataset:

• Real user prompts are rare in open datasets. Large LLM companies have them, but they are rarely shared with the open-source communities.
• Includes 122K conversations from reasoning models (o1-preview, o1-mini), which are real-world reasoning use cases (instead of synthetic ones) that often involve complex problem solving and are very costly to collect.

Access:

• Non-toxic public version: https://hf.co/datasets/allenai/WildChat-4.8M
• Full version (gated): https://hf.co/datasets/allenai/WildChat-4.8M-Full (requires justification for access to toxic data)
• Exploration tool: https://wildvisualizer.com (currently showing the 1M version; 4.8M update coming soon)

Original Source:

• https://x.com/yuntiandeng/status/1954929005305414062

Deep learning is revolutionizing industries by enabling computers to learn from complex data with remarkable accuracy. From training your first CNN to leveraging pre-trained LLMs, the fundamentals covered in this article provide a solid foundation for building AI solutions. By mastering tools like PyTorch, techniques like transfer learning, and applications in computer vision and NLP, you’re well-equipped to tackle real-world challenges. Whether creating a personalized doggy door or classifying fruit, deep learning opens a world of possibilities. Start experimenting, set up your AI environment, and join the global community driving innovation through deep learning.

https://open.substack.com/pub/ahmedgamalmohamed/p/fundamentals-of-deep-learning?r=58fr2v&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true

hello, I have a research project about 911 calls, I need a dataset for 911 call audio to listen to them to analysis them and answer our research questions

if you know AI model to listen to calls and analyze them, please share it with me

also if there are publications about analysis of 911 audio calls, please share them with me

https://www.tiktok.com/t/ZTHs4sxuraarw-3LU8T/

I have a resource showing BT, HT, and hybrid GMO corn adoption in the years since 2000 and I want data that correlates with it somehow.

Examples:

-European Corn Borer Populations (By State)

-European Corn Borer Diversity/Species Richness (By State)

-European Corn Borer Larvae In Non-BT Corn (By State)

-European Corn Borer Larvae In (Crop other than BT Corn) By State

-Non-BT Corn Deaths Due to Insects

-(Crop other than BT corn) Deaths due to Insects

If anyone knows how to get data related to anything above, it would be a lot of help. It can be a species other than European Corn Borers and a crop other than corn. It can also be about weeds instead of insects.

Hello, I need the IAM handwritten text dataset, but when I registered on the website , the confirmation email never came. I tried with a different email, same issue. The one found on Kaggle is incomplete.
I was searching for a solution and realised that its a common issue. But the posts are from 2+ years ago. Does anyone have access to the dataset and can share it with me please?

We’ve been working on a desktop app called Crawbots — an all-in-one IDE for web data extraction. It’s designed to simplify the scraping process, especially for developers working with Puppeteer, Playwright, or Selenium.

We’re aiming to make Crawbots powerful yet beginner-friendly, so junior devs can jump in without fighting boilerplate or complex setups.

Would appreciate any thoughts, questions, or brutal feedback

i’m looking to create a dash board on local housing affordability for a university research center and was wondering if anybody knew of good, low cost real estate data at the listing level of detail.

ideally this data would be updated at least monthly

any tips? thanks!