DeepView
DeepView is a free, open-source deep learning model viewer and visual debugger. It allows users to upload their models and visualize the architecture, inspect data flowing through the network, visualize activations and gradients, and gain insights into the model.
DeepView: Free Deep Learning Model Viewer & Visual Debugger
Visualize deep learning models, inspect data flow, and gain insights with a free, open-source tool - upload your model and explore its architecture with DeepView.
What is DeepView?
DeepView is an open-source tool for visualizing and debugging deep learning models. It provides an intuitive graphical interface that allows users to easily upload their models built with frameworks like TensorFlow, PyTorch, and Keras.
Some key features of DeepView include:
- Model architecture visualization - See a graphical overview of your model's layers and connections between them to understand the full topology.
- Activation visualization - Visualize the activation outputs for different layers to see which features the network is learning.
- Gradient visualization - Inspect gradient values flowing backward through the network during training to debug issues.
- Data visualization - Sample data batches flowing through the neural network to ensure the model is processing data correctly.
- Layer inspection - Investigate detailed parameters and outputs for each layer in the model.
- Shareable model graphs and visualizations - Export diagrams and activation maps for documentation and analysis.
By uploading their models into DeepView, users can gain intuitions for how their models work under the hood, identify potential problems areas, and improve model performance. Its visual interface makes it easy for anyone to understand what’s happening inside deep neural networks.
DeepView Features
Features
- Visualize neural network architectures
- Inspect data flowing through the network
- Visualize activations and gradients
- Gain insights into model performance and training
Pricing
- Open Source
Pros
Free and open source
Easy to use GUI
Model agnostic - works with TensorFlow, PyTorch, Keras, etc
Help debug model training issues
Interactive visualization
Cons
Limited to smaller models due to browser limitations
Less advanced than commercial model visualization tools
Requires coding to integrate models rather than drag and drop interface
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