Build better models faster with Weights & Biases, the leading developer-first MLOps platform
Unlock your machine learning team’s productivity by optimizing, visualizing, collaborating on, and standardizing their model and data pipelines – regardless of framework, environment, or workflow. Weights & Biases streamlines MLOps for machine learning and deep learning workloads on AWS, whether on Amazon SageMaker or running your own machine learning on AWS infrastructure.
Explore the Weights & Biases platform
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Smart farming with BlueRiver Technologies
John Deere subsidiary, BlueRiver Technologies, leverages Weights & Biases MLOps to accelerate building computer vision models for weed detection for targeted crop spraying.
# Flexible integration for any Python script
import wandb
# 1. Start a W&B run
wandb.init(project=’gpt3′)
# 2. Save model inputs and hyperparameters
config = wandb.config
config.learning_rate = 0.01
# Model training here
# 3. Log metrics over time to visualize performance
wandb.log({“loss“: loss})
Integrate with W&B with a few lines of code
Streamline your MLOps for your machine learning workloads on Amazon SageMaker. Users can integrate Weights & Biases with just a couple lines of Python code.
Use W&B with SageMaker
We made Weights & Biases to be flexible and easy to use, regardless of your framework or workflow. Click the link below to read an text classification tutorial with SageMaker, Hugging Face, and W&B.
