DeepSharp
The best of three worlds: TensorFlow's way of describing a network, PyTorch's way of running it, and ML.NET's way of learning from a table. Deep learning in C#: the layer over the engines that already exist. Describe, train and use a network in C# — layers, losses, optimizers and a training loop with early stopping and checkpoints, in Keras's words or written as code — while the arithmetic runs on .NET's own vector maths, behind a seam a heavier engine such as libtorch through TorchSharp can stand behind without a line of your model changing. And a table that a tree learns better than a network does not have to become one: the same prepared data is meant for ML.NET's trainers too. DeepSharp provides what an engine does not: the model's shape, the path your data takes into it, the training loop, the checkpoints and the charts.
Activity
- Latest release
- 4d ago
- Total releases
- 17
- Cadence
- ~daily
- Last 12 months
- 17
Details
- License
- MIT
- First release
- Sep 23, 2026
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0.16.0
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0.15.0
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0.14.0
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0.13.0
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0.12.0
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0.11.0
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0.10.0
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0.9.0
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0.8.0
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0.7.1
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0.7.0
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0.6.1
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0.5.0
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0.4.0
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0.3.0
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0.2.0
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0.1.0
initial
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