The next generation of ML development
PerceptiLabs is a dataflow driven, visual API for TensorFlow, carefully designed to make machine learning (or deep learning) modeling as intuitive as possible.
Components in PerceptiLabs
Components in PerceptiLabs
- The components have settings that you can change and tune
- A component automatically generates a visualization of the output
- The visualizations update in real-time when you change the component settings
- The components auto-generate TensorFlow low-level code, which you can view and edit
Graph creation
Graph creation
- The dataflow is defined by connecting the components
- The model architecture is visualized as you are building your model output
- The shape of the inputs and outputs are automatically calculated, and configs/hyperparameters suggested, to quickly get you up and running
Debugging
Debugging
- PerceptiLabs shows you tips, warnings and errors while you are building your model
- Quickly see where something is wrong and fix it
- Debug the model and the code Get instant feedback to better understand your model
Advanced statistics view during training
Advanced statistics view during training
- Real-time granular visualizations
- Get an overview of the model performance and predictions
- Visualize each components variables, such as weights, biases, gradients and outputs
- Real-time debugging example: Understand the gradients if it is vanishing or exploding and where in the model it happens