Visualizer for neural network, deep learning and machine learning models
Repository Index
47,133 repositories indexed
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♾ 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
Scalable and user friendly neural :brain: forecasting algorithms.
- deep-learning
- forecasting
- esrnn
- nbeats
Python Toolkit for Causal and Probabilistic Reasoning
- python
- bayesian-networks
- causal-inference
- causal-discovery
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
- pytorch
- graph-neural-networks
- temporal-networks
- temporal-graphs
React data visualization library for streaming, networks, and AI-assisted development
- nteract
- visualization
- d3
- react
TensorFlow Tutorials
- tensorflow-tutorials
- convolutional-neural-networks
- recurrent-neural-networks
PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer
- graph
- visualization
- gpu
- graphistry
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
A curated list of community detection research papers with implementations.
- graph-clustering
- network-clustering
- clustering
- dimensionality-reduction
A toolkit to make debugging iOS applications easier 🚀
Implementing a Neural Network from Scratch
Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
- python
- genetic-algorithm
- optimization
- numpy
A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).
An experimentation and research platform to investigate the interaction of automated agents in an abstract simulated network environments.
Graph and network visualization using tabular data in R
- r
- network-graph
- graph
- visualization
Synthetic data generators for tabular and time-series data
- gan-architectures
- gan
- deep-learning
- synthetic-data
What's in your data? Extract schema, statistics and entities from datasets
- python
- privacy
- pii
- npi
Koç University deep learning framework.
- knet
- deep-learning
- julia
- machine-learning
A collection of computer vision pre-trained models.