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Showing 3 open source projects for "ssh"

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Machine Learning Python Clear Filters & Widen Search

Automate contact and company data extraction
Build lead generation pipelines that pull emails, phone numbers, and company details from directories, maps, social platforms. Full API access.

Generate leads at scale without building or maintaining scrapers. Use 10,000+ ready-made tools that handle authentication, pagination, and anti-bot protection. Pull data from business directories, social profiles, and public sources, then export to your CRM or database via API. Schedule recurring extractions, enrich existing datasets, and integrate with your workflows.

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Simplify Purchasing For Your Business
Manage what you buy and how you buy it with Order.co, so you have control over your time and money spent.

Simplify every aspect of buying for your business in Order.co. From sourcing products to scaling purchasing across locations to automating your AP and approvals workstreams, Order.co is the platform of choice for growing businesses.

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1

lightning AI

The most intuitive, flexible, way for researchers to build models

...Find templates (Lightning Apps), modify them and publish your own. Lightning Apps can even be full standalone ML products! Run on your laptop for free! Download the code and type 'lightning run app'. Feel free to ssh into any machine and run from there as well. In research, we often have multiple separate scripts to train models, finetune them, collect results and more.

Downloads: 3 This Week

Last Update: 2025-11-28
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2

Guild AI

Experiment tracking, ML developer tools

...The toolkit is platform-agnostic, running on all major operating systems and integrating seamlessly with existing software engineering tools. Guild AI supports various remote storage types, including Amazon S3, Google Cloud Storage, Azure Blob Storage, and SSH servers.

Downloads: 0 This Week

Last Update: 2024-11-13
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3

ML workspace

All-in-one web-based IDE specialized for machine learning

...This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard) perfectly configured, optimized, and integrated. Usable as remote kernel (Jupyter) or remote machine (VS Code) via SSH. Easy to deploy on Mac, Linux, and Windows via Docker. Jupyter, JupyterLab, and Visual Studio Code web-based IDEs.By default, the workspace container has no resource constraints and can use as much of a given resource as the host’s kernel scheduler allows.

Downloads: 0 This Week

Last Update: 2022-07-12
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