ML Experiment Tracker
Plan reproducible ML experiment runs with parameters and metrics tracking
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Plan reproducible ML experiment runs with parameters and metrics tracking
Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.
Azure Weights & Biases SDK for .NET. ML experiment tracking and model management via Azure Marketplace. Use for creating W&B instances, managing SSO, marketplace integration, and ML observability.
Machine learning engineer expert for PyTorch, scikit-learn, model evaluation, and MLOps
Weights & Biases integration skill for experiment tracking, hyperparameter sweeps, and artifact versioning.
Monitor and analyze Weights & Biases training runs. Use when checking training status, detecting failures, analyzing loss curves, comparing runs, or monitoring experiments. Triggers on "wandb", "training runs", "how's training", "did my run finish", "any failures", "check experiments", "loss curv...
Azure Weights & Biases SDK for .NET. ML experiment tracking and model management via Azure Marketplace. Use for creating W&B instances, managing SSO, marketplace integration, and ML observability.
Facilitates ML experiment tracking and model management using Azure Weights & Biases SDK for .NET.
Facilitates ML experiment tracking and model management using Azure Weights & Biases SDK for .NET, enhancing ML observability.
Agent skill for ML / AI Engineer, Data Scientist, Backend Developer, published by Rudson-Oliveira. Project details and file access are provided by the publisher.
Agent skill for ML / AI Engineer, Data Scientist, Backend Developer, published by ranbot-ai. Project details and file access are provided by the publisher.
Agent skill for ML / AI Engineer, Data Scientist, Backend Developer, published by mayurrathi. Project details and file access are provided by the publisher.
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