Fostering Data Exploration and Modeling with Synthetic Datasets
The SynthDataHub project addresses critical challenges in the data science community. By offering realistic synthetic datasets, it promotes hands-on learning and experimentation in a risk-free environment. This initiative is especially valuable for learners, researchers, and professionals who seek diverse datasets for honing their skills, testing hypotheses, and developing and validating machine learning models. Additionally, the collaborative nature of the platform encourages knowledge sharing, fostering a vibrant community that pushes the boundaries of data science and machine learning.
Usage Guidelines - The synthetic datasets provided by SynthDataHub are freely available for use in learning, research, and development endeavors. Users are encouraged to explore, analyze, and model with these datasets to enhance their skills and understanding of data science and machine learning. When utilizing the datasets, it is required that proper credit is given to the creator of the dataset. This acknowledgment ensures the continued support and growth of the SynthDataHub community.
Disclaimer - While every effort is made to create synthetic datasets that mimic real-world environment data, users are advised that these datasets are inherently artificial and may not fully capture the complexities of actual real-world environment. The creators of SynthDataHub are not liable for any consequences arising from the use of the synthetic datasets. Users are encouraged to exercise discretion and validate findings against real-world data where applicable.
Synthetic Datasets
- Agroecology Impact Dataset
- Agroforestry Impact Dataset
- Climate-Resilient Agriculture Dataset
- Crop Diversity and Resilience Dataset
- Crop Yield dataset
- Food Supply Chain Sustainability Dataset
- Gender-Inclusive Agriculture Dataset
- Precision Agriculture Dataset
- Smallholder Farming Dataset
- Soil Health and Fertility Dataset
- Cyber Campaigns Dataset
- Cybersecurity Incidents Dataset
- Indicators of Compromise (IoCs) Dataset
- Malware Dataset
- Threat Actors Dataset
- Tactics, Techniques, and Procedures (TTPs) Dataset
- Vulnerabilities Dataset
- CPU Processing Power Dataset
- Network Performance Dataset
- Network Traffic for Intrusion Detection Dataset
- Software Defects Dataset
Hello Data Enthusiasts! 👩💻👨💻 We're happy to see the community benefiting from our open source synthetic datasets! 🚀 If you use our datasets in your projects, research, or applications, we kindly request that you give credit to the source—us! 🙏
Here's a simple guide:
- 🌟 Mention us in your acknowledgments.
- 📚 Include a reference to our project in your documentation or publications.
- 📢 Share the love! Let others know where they can access these awesome datasets.
Cite this work as: Nti, I. K., Dzamesi, L., & Reddy, G. S. D. (2024). SynthDataHub: Fostering Data Exploration and Modeling with Synthetic Datasets. https://doi.org/10.13140/RG.2.2.18173.13282
- Do you have any ideas for improvement? We'd love to hear them! Please open an issue and share it with us.
Help fuel our open-source mission if you like what you see, give us a star ⭐ and share the love, we love seeing our community thrive. Your support helps us grow and continue providing valuable resources to the community. 🌐✨