---
language:
- en
license: cc-by-4.0
tags:
- books
- pdf
- textbooks
- educational
- computer-science
- mathematics
- machine-learning
- philosophy
size_categories:
- 1K<n<10K
---

# 📚 PDF Books Collection with Metadata

## Dataset Description

This dataset contains **1043 PDF textbooks and educational materials** (13.56 GB) covering various technical and philosophical topics.

### 🎯 Topics Covered

- **Computer Science**: Programming, Algorithms, Operating Systems, Software Engineering
- **Mathematics**: Calculus, Algebra, Geometry, Statistics, Mathematical Thinking
- **Artificial Intelligence**: Machine Learning, Deep Learning, Neural Networks, LLMs, ChatGPT
- **Data Science**: Analytics, Visualization, Data Mining
- **Physics**: Quantum Mechanics, Theoretical Physics, Universe & Cosmology
- **Buddhism & Philosophy**: Zen, Meditation, Buddhist Thought, Critical Thinking
- **Networking**: IoT, Cloud Computing, 5G, Infrastructure
- **Security**: Cryptography, Forensics, Cybersecurity

### 📁 Dataset Structure

Each row in the dataset contains:

```python
{
    'file_name': str,      # Original PDF filename
    'title': str,          # Book title
    'author': str,         # Author(s) - may be empty
    'subject': str,        # Subject/topic - may be empty
    'language': str,       # Language code - may be empty
    'category': str,       # Auto-categorized topic (if available)
    'pdf': bytes          # The actual PDF file content
}
```

### 💻 Usage

#### Load the entire dataset:

```python
from datasets import load_dataset

# Load dataset
dataset = load_dataset("YOUR_USERNAME/pdf-books-collection")

# Access a book
book = dataset['train'][0]
print(f"Title: {book['title']}")
print(f"Author: {book['author']}")

# Save PDF to disk
with open(f"{book['file_name']}", 'wb') as f:
    f.write(book['pdf'])
```

#### Stream for large datasets:

```python
# Stream without downloading everything
dataset = load_dataset("YOUR_USERNAME/pdf-books-collection", streaming=True)

# Iterate through books
for book in dataset['train']:
    print(book['title'])
    # Process or save as needed
```

#### Filter and search:

```python
# Load as pandas for easy filtering
df = dataset['train'].to_pandas()

# Find machine learning books
ml_books = df[df['title'].str.contains('Machine Learning', case=False)]

# Find books by author
author_books = df[df['author'].str.contains('Russell', case=False)]

# Filter by category
ai_books = df[df['category'] == 'AI & Machine Learning']
```

### 📊 Statistics

- **Total Books**: 1043
- **Total Size**: 13.56 GB
- **Format**: PDF
- **Languages**: Primarily English
- **Metadata Completeness**: 
  - Titles: 100% (extracted or from filename)
  - Authors: ~65%
  - Subjects: ~40%
  - Languages: ~20%

### 🎓 Educational Use Cases

1. **Building a Personal Library System**: Create searchable digital library
2. **Research & Study**: Quick access to textbooks across multiple domains
3. **Machine Learning Projects**: 
   - Document classification
   - OCR and text extraction
   - Semantic search implementation
   - RAG (Retrieval Augmented Generation) systems
4. **Educational AI**: Training material for educational chatbots
5. **Bibliography Analysis**: Study trends in technical literature

### ⚖️ Legal & Ethical Considerations

**IMPORTANT**: This dataset contains copyrighted educational materials. Users should:

- ✅ Use for personal study and research
- ✅ Verify copyright status before commercial use
- ✅ Respect author and publisher rights
- ❌ Not redistribute commercially without permission
- ❌ Not use for piracy or copyright infringement

This collection is shared for **educational and research purposes** under fair use principles. If you are a copyright holder and want content removed, please contact the dataset maintainer.

### 🔧 Technical Details

- **Extraction Method**: PyPDF2 for metadata extraction
- **Storage Format**: Parquet with binary PDF column
- **Hosting**: Hugging Face Datasets (Community Tier)
- **Access**: Public dataset, free to download

### 📝 Citation

If you use this dataset in your research or projects, please cite:

```bibtex
@dataset{pdf_books_collection_2025,
  author = {Your Name},
  title = {PDF Books Collection with Metadata},
  year = {2025},
  publisher = {Hugging Face},
  howpublished = {\url{https://huggingface.co/datasets/YOUR_USERNAME/pdf-books-collection}}
}
```

### 🤝 Contributing

Found an error in metadata? Want to add more books? Please open an issue or pull request!

### 📧 Contact

For questions, issues, or takedown requests, please open an issue in this repository.

---

**Note**: This is a community-contributed dataset. The maintainer is not responsible for the copyright status of individual files. Users are responsible for ensuring their use complies with applicable laws and regulations.