EvalML builds, optimizes, and evaluates machine learning pipelines with automated data checks and objective functions.
Open source
24 alternativesKnet
Knet provides a deep learning framework developed at Koç University for building models.
About Knet
Knet is the Koç University deep learning framework implemented in Julia by Deniz Yuret and collaborators. It supports GPU operation and automatic differentiation using dynamic computational graphs for models defined in plain Julia, and installs with Pkg.add("Knet").
It includes a tutorial, examples such as LeNet for MNIST handwritten digit recognition, and machine images for AWS, Singularity and Docker. Bugs are handled through GitHub issues, with help and development discussion through mailing lists and Slack.
Key features
- Supports GPU operation for models defined in plain Julia
- Automatic differentiation using dynamic computational graphs
- Installs in Julia with using Pkg; Pkg.add("Knet")
- Includes tutorial and examples such as LeNet for MNIST
- Provides machine images for AWS, Singularity and Docker
- Connected to KnetML organization with models and tutorials
Best for: Julia users building deep learning models with GPU support and dynamic computational graphs.
Good for
- Supports GPU operation and automatic differentiation in plain Julia
- Provides tutorial, examples, and machine images for AWS, Singularity and Docker
Knet at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Knet FAQ
How do I install Knet?
At the Julia prompt run: using Pkg; Pkg.add("Knet").
How do I report a bug?
Open a GitHub issue.
Where can I ask for help or request a feature?
Join the knet-users mailing list.
Is something wrong or out of date?
Tell us and an editor will check it.
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