NN-SVG
aws-mlu-explain
| NN-SVG | aws-mlu-explain | |
|---|---|---|
| 4 | 3 | |
| 4,427 | 377 | |
| - | 3.7% | |
| 3.4 | 7.2 | |
| 27 days ago | 5 months ago | |
| JavaScript | JavaScript | |
| MIT License | GNU General Public License v3.0 or later |
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NN-SVG
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NN-SVG
Yeah, the github repo is a much better link for this, as it explains what it is. https://github.com/alexlenail/NN-SVG
- NN-SVG is a tool for creating Neural Network architecture drawings parametrically rather than manually! It also provides the ability to export those drawings to Scalable Vector Graphics (SVG) files, suitable for inclusion in academic papers or web pages
- Visualize Neural Networks with this Cool NN SVG tool!
aws-mlu-explain
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For Amazon, I Made A Web-based, Interactive/Visual Explainer of Decision Trees in Machine Learning
Posting here as it was created using JavaScript. D3.js for the visuals, parcel for the bundler, and IntersectionObserver for the scrolls. All code available here: https://github.com/aws-samples/aws-mlu-explain
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Smooth transition for presentation slides
HTML, CSS, JavaScript. Here is the repository with source code for the presentation, if you want to look into it
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Amazon’s Visual, Interactive Explainer on The Bias Variance Tradeoff
It's d3.js, their source code is available https://github.com/aws-samples/aws-mlu-explain/tree/main/bias-variance
What are some alternatives?
Sketch_Recognizer_Ai - Artificial intelligence is used in the project to predict what are you drawing.
netron - Visualizer for neural network, deep learning and machine learning models
NeuralNetworkPlayground - A website in which you can customize, train and visualize changes in your neural networks as they learn. You can also upload your own datasets and change any parameters
clearml - ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
ml5-library - Friendly machine learning for the web! 🤖
best_AI_papers_2021 - A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.