Visualizer for neural network, deep learning and machine learning models
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The modern link attribution platform. Loved by world-class engineering teams at Twilio, Zillow, Jobber, Vercel, Raycast, and more.
- vercel
- nextjs
- upstash
- tinybird
Empowering People Ethically 🚀 — Matomo is hiring! Join us → https://matomo.org/jobs Matomo is the leading open-source alternative to Google Analytics, giving you complete control and built-in privacy. Easily collect, visualise, and analyse data from websites & apps. Star us on GitHub ⭐️ – Pull Requests welcome!
The Cloud Native AI Platform
- ml
- kubernetes
- minikube
- tensorflow
Kubernetes Community Documentation
♾ A Graph Visualization Framework in JavaScript.
- graph-drawing
- tree
- network
- graph
Graph theory (network) library for visualisation and analysis
- cytoscapejs
- graph-theory
- visualisation
- analysis
Learning Convolutional Neural Networks with Interactive Visualization.
- deep-learning
- visualization
- interactive-visualizations
- visual-learning
🦄 Sourcerer app makes a visual profile from your GitHub and git repositories.
- sourcerer
- profile
- kotlin
- git
A scikit-learn compatible neural network library that wraps PyTorch
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
- cntk
- visualization
- tensorflow
- model-converter
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
links to conference publications in graph-based deep learning
- graph-neural-networks
- graph-convolutional-networks
- graph
- deep-learning
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
- tensorflow
- machine-learning
- regression
- convolutional-neural-networks
Radzen Blazor is the most sophisticated free UI component library for Blazor, featuring 155+ native components including DataGrid, Scheduler, Charts, and advanced theming with full support for Material Design and Fluent UI. If Radzen Blazor is useful to you, a ⭐ on GitHub helps other Blazor developers find it.
- blazor
- asp-net-core
- blazor-components
- blazor-application
Scalable and user friendly neural :brain: forecasting algorithms.
- deep-learning
- forecasting
- esrnn
- nbeats
N-D labeled arrays and datasets in Python
A curated list of awesome network analysis resources.
- network-analysis
- network-visualization
- complex-networks
- political-networks
ACID Document Database
Math.NET Numerics
- math
- numerics
- linear-algebra
- fsharp
AI Infra / AI Orchestration / AI Control Plane
In-memory dimensional time series database.
🛠 All-in-one web-based IDE specialized for machine learning and data science.
A cross-platform plotting library for .NET