Evening! 🫡

Just uploaded Open-MalSec v0.1, an early-stage open-source cybersecurity dataset focused on phishing, scams, and malware-related text samples.

📂 This is the base version (v0.1)—just a few structured sample files. Full dataset builds will come over the next few weeks.

🔗 Dataset link: huggingface.co/datasets/tegridydev/open-malsec

🔍 What’s in v0.1?

A few structured scam examples (text-based)
Covers DeFi, crypto, phishing, and social engineering
Initial labelling format for scam classification

⚠️ This is not a full dataset yet. Just establishing the structure + getting feedback.

📂 Current Schema & Labelling Approach

Each entry follows a structured JSON format with:

“instruction” → Task prompt (e.g., “Evaluate this message for scams”)
“input” → Source & message details (e.g., Telegram post, Tweet)
“output” → Scam classification & risk indicators

Sample Entry

json { “instruction”: “Analyze this tweet about a new dog-themed crypto token. Determine scam indicators if any.”, “input”: { “source”: “Twitter”, “handle”: “@DogLoverCrypto”, “tweet_content”: “DOGGIEINU just launched! Invest now for instant 500% gains. Dev is ex-Binance staff. #memecrypto #moonshot” }, “output”: { “classification”: “malicious”, “description”: “Tweet claims insider connections and extreme gains for a newly launched dog-themed token.”, “indicators”: [ “Overblown profit claims (500% ‘instant’)”, “False or unverifiable dev background”, “Hype-based marketing with no substance”, “No legitimate documentation or audit link” ] } }

🗂️ Current v0.1 Sample Categories

Crypto Scams → Meme token pump & dumps, fake DeFi projects

Phishing → Suspicious finance/social media messages

Social Engineering → Manipulative messages exploiting trust

🔜 Next Steps

🔍 Planned Updates:

Expanding dataset with more phishing & malware examples

Refining schema & annotation quality

Open to feedback, contributions, and suggestions

If this is useful, bookmark/follow the dataset here:

🔗 huggingface.co/datasets/tegridydev/open-malsec

More updates coming as I expand the datasets 🫡

💬 Thoughts, feedback, and ideas are always welcome! Drop a comment or DMs are open 🤙

I`m trying to make a project with creating an OCR model for Ukrainian cursive recognition. I found one dataset with seperate Ukrainian letters, but I can`t fing a dataset with words, sentences, texts e.t.c. Help me please^(

The dataset was processed and published on the Metabase BI platform.
It can be useful for research purposes.
Unfortunately, it’s closed under the simple registration as it might go down due to high load.
UK Dataset

What platforms can you get datasets from?

Instead of Kaggle and Roboflow

[Sorry for my bad English. English is not my native language.]

Hello,

I am currently a student studying computer engineering. I need to do a graduation project in order to graduate. Since I have worked on NLP a lot before, I want my graduation project to be about NLP. I plan to develop a model that tries to identify the psychological disorders these people have, based on the writings written by people with psychological disorders.

However, I am having difficulty at the first stage. I have not been able to find a dataset to classify for a week. This is the only data set that can be useful to me, but it is not enough for me. reddit mental health data

I tried creating artificial datasets, but they didn’t give the results I wanted. What can I do about this?

Thank you very much in advance for your help.

I downloaded the 449M zip file that contains csv files. The branded_food.csv file has a column for the brand name but it’s bank. For example there are rows of products for PEPPERIDGE FARM but it’s not telling what products for PEPPERIDGE FARM.

Are there other sources I can download from which have more complete data?

I am looking for data like the nutritional label that’s in the back of every packaged food.

Looking for a large dataset of different foods spectral data, one containing nutritional information would be good, but the more datasets the better as I can just guess the rough nutritional data through the food name, as this isn’t for a precise purpose

Just getting into data analytics and decided that I wanted to create my own project to practice. Looking for Portland, Oregon job market data. Hopefully something in the range of 2020 – 2024. Any suggestions or links?

I need to replicate the below paper in which the dataset in title has been used.

The paper: Goldwater, S., Jurafsky, D., & Manning, C. D. (2010). Which words are hard to recognize? Prosodic, lexical, and disfluency factors that increase speech recognition error rates. Speech Communication, 52(3), 181–200.

Hi everyone,

I’m working on a research project comparing LLM-generated text with human-written text. Does anyone know of a validated dataset (with DOI) that includes both? If not, could you share tips on creating one?

LLM text: Best models/prompts to generate diverse samples? Human text: Reliable sources for high-quality text? Validation: How to ensure balance and avoid bias?

Any help or pointers would be greatly appreciated! Thanks in advance.

Hello, I want to make a website using Trader Joe’s products. Is there any way to access the list directly through their website? Otherwise, are there any public datasets? I just need information like the product name and picture.

Hi , I’m currently working on a Food Nutrition App for my final year project , I’m having a hard time finding datasets of food with their nutritional values including pictures . Please help if you have any suggestions for website .

Like title, hoping for a recent dataset with a large amount of games, ideally from the premiere league. I wish for there to be player locations with each action, such as their location when they took a shot. Ideally it would be consistently updated, however that is not necessary.

For example I am looking for a dataset similar to the one used in this analysis:
https://www.kaggle.com/code/usamawaheed/expected-goals-xg-model/notebook

Thank you all

Please recommend free Historic Weather Datasets

Where does this data come from?

Amazon.com features a best-sellers listing page for every category, subcategory, and further subdivisions.

I accessed each one of them. Got a total of 25,874 best seller pages.

For each page, I extracted data from the #1 product detail page – Name, Description, Price, Images and more. Everything that you can actually parse from the HTML.

There’s a lot of insights that you can get from the data. My plan is to make it public so everyone can benefit from it.

I’ll be running this process again every week or so. The goal is to always have updated data for you to rely on.

Where does this data come from?

Rating: Most of the top #1 products have a rating of around 4.5 stars. But that’s not always true – a few of them have less than 2 stars.

Top Brands: Amazon Basics dominates the best sellers listing pages. Whether this is synthetic or not, it’s interesting to see how far other brands are from it.

Most Common Words in Product Names: The presence of “Pack” and “Set” as top words is really interesting. My view is that these keywords suggest value—like you’re getting more for your money.

Raw data:

You can access the raw data here: https://github.com/octaprice/ecommerce-product-dataset.

Let me know in the comments if you’d like to see data from other websites/categories and what you think about this data.

Hi, I’m looking for a dataset in CSV form that contains sequential game logs of player actions, either individual actions or completed goals (such as completing a level then moving on to the next level, quitting the game or choosing another activity within the game). I’m looking to build a model that predicts the action a player will take based on past in-game actions.

I’m a bit confused about something with the [RAVDESS Emotional Speech Audio] dataset. I noticed that the file numbers on Kaggle don’t match the original dataset on Zenodo. From the original source, there should be 192 files per class (spread across 8 emotions: Neutral, Calm, Happy, Sad, Angry, Fearful, Disgust, Surprised).

But in the Kaggle version:

Most classes (like Happy, Sad, etc.) have 384 files instead of 192.

Two classes (Neutral and Calm) have around 2544 files, which is a lot more than expected.

Has anyone else noticed this? Could this be due to changes made by the uploader, or is there another reason? Would love to hear if anyone has more context!

Hi I am looking for sensitive pii and non sensitive pii dataset.

Like shown in below format:

Attribute_name, description, label full_name, The full name of individual used for identification, Non-Sensitive PII

Can anyone help me please?

Hey guys,
I have been switching my focus to Machine Learning recently as my main point of study in school. I am currently in search of a project. My idea was to create a flight price predictor that focuses more on PURCHASE DATE then anything else. My idea was to get data (it can be historical or present), that tracks how prices of specific flights changed depending on day of purchase rather than the normal factors of travel dates themselves.

I understand the trend of prices increasing as time of flight comes closer is common knowledge. However, I am curious if a ML model could find a pattern. very few tools, other then Hopper, give you insight into whether you should purchase your ticket now or wait for a cheaper price. And even Hopper just gives the advice, it does not provide much insight into just how the price will change.

Where can I find the data I need? Seems like there may be issues with data like this as airlines won’t want to give it up?

I am trying to build a simple gui and easy to operate python app for image auditing and tamper detection. I need the exif data to build a list of resolutions connected to specific cameras ( there might be more than one that matches the resolution but still ). If anyone can provide any useful dataset or resource I will be really grateful

Hi there!

I’m a data science practitioner and I’ve some projects going on about Japan. Recently I’d like to do more hands on projects about Japan and have found very little dataset resorces. I usually use kaggle as a good starting point to get some ideias, but when it comes to Japan most of it is about videogames, and the majority of them are out of date. Any suggestions? I don’t really have a subject at the moment but using it to get familiarized.

Hi guys, has anyone worked with SportsMOT dataset? If yes, is it possible to give me your dataloader?

pls help me with dataset for relevant and valid tech course links specific to each job role

I want to write a data analytics code to map and visualize the sectors, braking zones, etc for different tracks. Where can I find the data for doing this?

I used Icrawler and Selenium to download 400 images of button mushroom for my data set but it always download 50 images I use the fruit 360 dataset that have 400 images and don’t want to have impalance in my data

Made this Google extension that generates professional and insightful Google Slides presentations from a dataset in Google Sheets. It also outputs Google Docs and DOCX formats. Slides are compelling though because there is a theme library for users so it’s presentation-ready. My big challenge is that in order to get value out of it, people need a dataset. I was thinking of adding a resource section that links out to different ways to get a dataset. Everything from form tools, to other extensions that sync app data to sheets, to a directory of scrapers. What else should I add to that list to reduce the time-to-value?

Hello everyone, I’m working in a NLP project regarding which I need datasets in bodo, santali and maithili language. If anyone has any reference regarding it, can you please share, it will be quite helpful.