Create and validate structured metadata for datasets
Upload files to a Hugging Face repository
Convert PDFs to a dataset and upload to Hugging Face
Browse a list of machine learning datasets
Save user inputs to datasets on Hugging Face
Launch and explore labeled datasets
Label data for machine learning models
Manage and analyze labeled datasets
Display trending datasets and spaces
Provide feedback on AI responses to prompts
Transfer datasets from HuggingFace to ModelScope
Organize and process datasets for AI models
Research Tracker is a tool designed to assist in organizing and managing research projects, particularly in the realm of dataset creation. It helps users streamline their workflow, track progress, and maintain consistency throughout their research endeavors.
• Dataset Organization: Easily manage and categorize datasets for efficient access.
• Collaboration Support: Invite team members to collaborate on projects in real-time.
• Version Control: Track changes and maintain different versions of your datasets.
• Tagging System: Label datasets for quick identification and retrieval.
• Progress Tracking: Monitor the status of ongoing projects and set milestones.
• Data Cleaning Tools: Built-in features to preprocess and refine datasets.
• Integration: Compatible with popular data analysis platforms.
• Reporting Dashboard: Generate summaries and visualizations of your research progress.
How do I install Research Tracker?
Research Tracker is a web-based tool, so no installation is required. Simply sign up on the platform and start using it.
Can I collaborate with multiple team members?
Yes, Research Tracker allows you to invite multiple team members to collaborate on projects, with real-time updates and role-based access control.
What types of data formats are supported?
Research Tracker supports popular data formats such as CSV, Excel, JSON, and more. For a full list of supported formats, refer to the platform's documentation.