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Track Model Performance with Weights & Biases
Lavanya ShuklaFeb 17Beginner, Domain Agnostic, scikit-learn, Tutorial, W&B Meta, Plots, Sweeps, Kaggle
Curriculum Learning in Nature Using the iNaturalist 2017 Dataset
Stacey SvetlichnayaFeb 08Intermediate, Computer Vision, Object Detection, Experiment, CNN, Plots, iNaturalist
Classify the Natural World with Weights & Biases
Stacey SvetlichnayaFeb 08Advanced, Computer Vision, Object Detection, Keras, Experiment, CNN, Plots, ImageNet, iNaturalist, Exemplary
Hyperparameters of a Simple CNN Trained on Fashion MNIST
Stacey SvetlichnayaFeb 07Intermediate, Computer Vision, Object Detection, Experiment, CNN, Slider, Sweeps
Semantic Segmentation: The View from the Driver's Seat
Stacey SvetlichnayaFeb 06Advanced, Computer Vision, 3D, Object Detection, Semantic Segmentation, fastai, Experiment, CNN, ResNet, U-Net, Github, Panels, Plots, Slider, Sweeps, Berkeley Deep Drive, Autonomous Vehicles, Exemplary
Harness the Sky: Aerial Segmentation Benchmark with DroneDeploy
Stacey SvetlichnayaFeb 03Computer Vision
Introduction to Hyperparameter Sweeps – A Model Battle Royale To Find The Best Model In 3 Steps
Lavanya ShuklaFeb 02W&B Features
Debugging Neural Networks with PyTorch and W&B Using Gradients and Visualizations
Ayush ThakurJan 26PyTorch
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