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Distributed Training in tf.Keras With Weights & Biases
Sayak PaulApr 09Advanced, Domain Agnostic, Keras, Tutorial, MobileNet v2, Github, Plots, Distributed Training
Kaggle Starter Kernel: Jigsaw Multilingual Toxic Comment Classification
Sayak PaulApr 07Intermediate, NLP, Classification, scikit-learn, Tutorial, CNN, DistilBERT, Panels, Plots, Kaggle
Digging Into KITTI With Weights & Biases With PyTorch-Lightning Kitti
Boris DaymaMar 29Intermediate, Computer Vision, Object Detection, Semantic Segmentation, PyTorch Lightning, Experiment, Github, Plots, Sweeps, KITTI, Autonomous Vehicles
Visualizing and Debugging Neural Networks with PyTorch and Weights & Biases
Lavanya ShuklaMar 25Beginner, Domain Agnostic, Object Detection, PyTorch, Experiment, Panels, Plots, Sweeps, MNIST
Understanding State of the Art in Deep Learning: 3D Semantic Segmentation
Nicholas BardyFeb 22Intermediate, Computer Vision, 3D, Semantic Segmentation, Experiment, U-Net, Plots, ShapeNet
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
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