AndreyWhat is Dstack?
Define ML workflows as code and run via CLI. Use any cloud. Collaborate within teams.
Dstack is a tool in the Development & Training Tools category of a tech stack.
Key Features
Define ML workflows declaratively as codeRun workflows locally or remotely on any cloud (AWS, GCP, etc)Use on-demand on spot instances convenientlySave data, checkpoints, environments as artifacts and reuse them across workflowsNo need to use custom Docker images or Kubernetes
Dstack Pros & Cons
Pros of Dstack
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Cons of Dstack
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Dstack Alternatives & Comparisons
What are some alternatives to Dstack?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
