| | --- |
| | license: mit |
| | task_categories: |
| | - text-classification |
| | language: |
| | - en |
| | size_categories: |
| | - 1K<n<10K |
| | --- |
| | |
| | # 📦 SMS Spam Detection Dataset |
| |
|
| | A curated dataset of **SMS messages** labeled as **Spam** or **Ham (Not Spam)**. |
| | This dataset is ideal for building and testing **spam detection** models using Machine Learning or Deep Learning. |
| |
|
| | --- |
| |
|
| | ## 🧠 Overview |
| | - **File Name:** `spam.csv` |
| | - **Total Entries:** 5,000+ SMS messages |
| | - **Format:** CSV (Comma Separated Values) |
| | - **Columns:** |
| | - `label` → Indicates whether the message is **spam** or **ham** |
| | - `message` → The SMS text content |
| |
|
| | --- |
| |
|
| | ## 📊 Dataset Features |
| | | Feature | Description | |
| | |----------|-------------| |
| | | **Message Type** | Categorized as `spam` or `ham` | |
| | | **Text Content** | Real-world SMS messages | |
| | | **Balanced Data** | Contains a good mix of spam and non-spam messages | |
| | | **Cleaned Data** | Pre-processed and structured for ML usage | |
| |
|
| | --- |
| |
|
| | ## ⚙️ Use Cases |
| | - Spam Detection using ML or DL models |
| | - NLP Text Classification |
| | - Preprocessing and feature extraction (TF-IDF, Word2Vec, etc.) |
| | - Experimenting with model accuracy and F1-scores |
| |
|
| | --- |
| |
|
| | ## 📁 File Structure |
| | - `Dataset` —> `spam.csv` |
| | |
| | --- |
| |
|
| | ## 🧩 Example Rows |
| | | label | message | |
| | |--------|----------| |
| | | ham | Hey, are we still meeting today? | |
| | | spam | Congratulations! You’ve won a $1000 Walmart gift card! Click here to claim. | |
| |
|
| | --- |
| |
|
| | ## 📜 License(mit) |
| | This dataset is provided for **educational and research purposes only**. |
| |
|
| | --- |
| |
|
| | ## 🙌 Author |
| | **Gaurav Pandey (Mr. Def@ult)** |
| | Founder of **DarkNeuronAI** |
| | 📧 darkneuronai.official@gmail.com |
| |
|
| | --- |
| |
|
| | ## Developed With ❤️ By DarkNeuronAI |
