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Welcome to FloydHub!
Here you'll find comprehensive information for training and deploying your deep learning and AI applications with our platform. We do our best to make this documentation clear and user friendly, but if you have unanswered questions, please visit the community forum or email us.
The fastest way to get up and running is to use our quickstart guide, which walks through an entire FloydHub training job step-by-step. You'll create a new Project on the FloydHub web dashboard, connect it to a local directory on your computer, and then kick-off a job using the FloydHub CLI to train your deep learning model on FloydHub's GPU servers.
Frictionless data science¶
Why worry about provisioning GPUs, installing drivers, or managing software dependency hell? With FloydHub, we take care of your entire deep learning DevOps workflow - so you can focus on the data science.
Training a TensorFlow model using GPUs on the cloud is as simple as executing this command on your terminal:
floyd run --gpu --env tensorflow "python train.py"
Try it now with our quickstart guide.
Powerful workflow tools¶
Whether you're using our web dashboard or our command line interface, our tools make your work easier and your team more productive:
- Interactive Jupyter Notebook support with FloydHub Workspaces
- End-to-end version control for data science
- Full reproducibility of jobs
- Deploy models as REST endpoints to integrate with your apps
Productivity for teams¶
FloydHub's Team Plan is a collaborative tool for data science teams of all sizes:
- Centralized, secure hub for all your team's machine learning experiments
- Team management with roles-based permissioning
- Consolidated billing and usage tracking
- High priority customer support
We're here to help!¶
We're always happy to help with any questions you might have! Search our documentation or check answers to frequently asked questions. The FloydHub community forum is another place to ask questions, request features, or share cool Projects. For more help, send us an email.