Operationalize.ML.NET
netron
| Operationalize.ML.NET | netron | |
|---|---|---|
| 1 | 36 | |
| 1 | 26,355 | |
| - | - | |
| 5.8 | 9.9 | |
| 9 months ago | 3 days ago | |
| C# | JavaScript | |
| - | MIT License |
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Operationalize.ML.NET
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Operationalize TensorFlow Models With ML.NET
You can find the whole source code at https://github.com/mariusmuntean/Operationalize.ML.NET
netron
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Your 14-Day Free Trial Ain't Gonna Cut It
They're data-dependence graphs for a neural-network scheduling problem. Like this but way bigger to start with and then lowered to more detailed representations several times: https://netron.app/?url=https://github.com/onnx/models/raw/m... My home-grown layout engine can handle the 12k nodes for llama2 in its highest-level form in 20s or so, but its not the most featureful, and they only get bigger from there. So I always have an eye out for potential tools.
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What's the best PyTorch model visualization tool?
Netron seems to be the best that I've seen so far. https://github.com/lutzroeder/netron
- Visualizer for neural network, deep learning and machine learning models
- Netron: Visualizer for Machine Learning Models
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
In exploring open-source projects, I've come across several promising tools capable of managing deep-learning models for images. Significantly, tools such as NETRON provide visualization of neural networks, while SHAP can be used for evaluating the significance of outputs.
- Netron is a viewer for neural network, deep learning and machine learning models
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Operationalize TensorFlow Models With ML.NET
We need to find out the exact input and output tensor names. A tool like Netron makes this super easy. Open the original .tflite and/or the ONNX model in Netron and click the Model Properties button in the lower left corner.
- Netron: A viewer for neural network, deep learning and machine learning models
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Visualize PyTorch Models with NNViz
How is this different from e.g Netron https://github.com/lutzroeder/netron
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[P]Visualizing a neural network.
Netron (https://netron.app/) is the best and mostly used NN visualizer. Just save your model and then simply load it via netron to look its layers and weights. If you want a more complex visualization then you can also play with Zetane ( but its paid, also have a free version) engine.
What are some alternatives?
onnx - Open standard for machine learning interoperability
openpilot - openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for 250+ supported car makes and models.
tensorflow-onnx - Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
optimizer - Actively maintained ONNX Optimizer
models - Models and examples built with TensorFlow
pwnagotchi - (⌐■_■) - Deep Reinforcement Learning instrumenting bettercap for WiFi pwning.
PlotNeuralNet - Latex code for making neural networks diagrams
onnx-tensorflow - Tensorflow Backend for ONNX
Synaptic.js - architecture-free neural network library for node.js and the browser
aws-mlu-explain - Visual, Interactive Articles About Machine Learning: https://mlu-explain.github.io/
deepdetect - Deep Learning API and Server in C++14 support for Caffe, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE