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Example projects, walkthroughs, and tutorials of how to use Weights & Biases |
Explore examples for using Weights & Biases to:
- Track and visualize machine learning experiments
- Version datasets and models
- Instrument models using different frameworks like PyTorch and Scikit
Fork examples from our GitHub repo or browse the direct links here. Contact us at c@wandb.com to contribute an example to the list.
Description | Dashboard | Code |
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Track Model Performance | W&B link | Kaggle Kernel |
Visualize Model Predictions | W&B link | Kaggle Kernel |
Saving and Restoring Models | W&B link | Colab Notebook |
Compare System Metrics | W&B link | |
Hyperparameter Sweeps | W&B link | Colab Notebook |
Description | Dashboard | Code |
---|---|---|
Intro to PyTorch with W&B | W&B Dashboard | Colab Notebook |
PyTorch MNIST Colab | W&B Dashboard | Colab Notebook |
Colorizing CNN transforms B&W images to color | W&B Dashboard | Github Repo |
Yolo-2 Bounding Box | W&B Dashboard | Github Repo |
Reinforcement Learning | W&B Dashboard | Github Repo |
char-RNN to forecast text | W&B Dashboard | Github Repo |
Exploring ResNets With W&B | W&B Dashboard | Colab Notebook |
Exploring Neural Style Transfer Paper With W&B | W&B Dashboard | Github Repo |
Debugging Neural Networks with PyTorch | W&B Report | GitHub Repo |
PyTorch Lightning | W&B Report | Colab Notebook |
Semantic Segmentation with PyTorch Lightning | W&B Dashboard | Github Repo |
Description | Dashboard | Code |
---|---|---|
Intro to Keras with W&B | W&B Dashboard | Colab Notebook |
Intro to Convolutional Neural Networks with W&B | W&B Dashboard | Colab Notebook |
Colorizing CNN transforms B&W images to color | W&B Dashboard | Github Repo |
CNN Face emotion classifier | W&B Dashboard | Github Repo |
Mask RCNN semantic segmentation | W&B Dashboard | Github Repo |
Fine-tuning CNN on iNaturalist data | W&B Dashboard | Github Repo |
Semantic segmentation with U-Net | W&B Dashboard | Github Repo |
Effects of Weight Initialization on Neural Networks | W&B Dashboard | Colab Notebook |
Can Neural Image Generators Be Detected? | W&B Dashboard | |
Visualize Model Predictions | W&B Dashboard | Kaggle Kernel |
Track Model Performance | W&B Dashboard | Kaggle Kernel |
Visualize models in TensorBoard with Weights & Biases | W&B Dashboard | Colab Notebook |
Weights & Biases with TPUs | Colab notebook |
Description | Dashboard | Code |
---|---|---|
GAN to predict video frames | W&B Dashboard | Github Repo |
Tracking TensorFlow model performance | Github Repo | |
Training distributed TensorFlow models | Github Repo |
Description | Dashboard | Code |
---|---|---|
Classifying Simpson's characters | W&B Dashboard | Github Repo |
Semantic Segmentation | W&B Dashboard | Github Repo |
Description | Public Dashboard | Code |
---|---|---|
Intro to Sweeps with W&B | W&B Dashboard | Colab Notebook |
PyTorch Sweeps: Meaning and noise in hyperparameter search | Report | |
Running sweeps in python scripts | Github Repo | |
Using sweeps with MPI frameworks | Github Repo |
Description | Public Dashboard | Code |
---|---|---|
Visualize Scikit Models | W&B Dashboard | Colab Notebook |
Using W&B with XGBoost | Github Repo | |
Using W&B with an SVM | Github Repo |
Title | Link |
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Hugging Face Integration | Colab Notebook |