Weights & Biases
Weights & Biases

Weights & Biases

With a few lines of code, save everything you need to debug, compare and reproduce your models
Weights & Biases Overview

Experiment tracking, Datasetset tracking, Dataset visualization

Deploys On
  • Amazon Web Services
  • Google Cloud Platform
  • Microsoft Azure
  • Other Public Cloud
  • Kubernetes
  • Private Cloud or Datacenter
  • SaaS

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Learn More About Weights & Biases
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The Whys and Hows of Managing Machine Learning Artifacts with Lukas Biewald
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Managing ML Experiments with Weights and Biases
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Maintaining Model Lineage with Weights & Biases Model Registry with Weights & Biases
Weights & Biases Details
Benefits

Weights & Biases helps your ML team unlock their productivity by optimizing, visualizing, collaborating on, and standardizing their model and data pipelines – regardless of framework, environment, or workflow.

Think of W&B like GitHub for machine learning models. With a few lines of code, you can save everything you need to debug, compare and reproduce your models— architecture, hyperparameters, git commits, model weights, GPU usage, and even datasets and predictions.

W&B’s lightweight integrations work with any Python script, and you can sign up for a free account and start tracking and visualizing models in 5 minutes.

Features

• W&B's dashboard lets you track your experiments, see live updates on model performance, check for overfitting, reproduce your best performances, and more.
• Artifacts gives you a bird's eye view of every step of model development so you can understand which data and which models depend on each other
• Tables lets you actually *see*, organize, and evaluate your data, unlocking insights about where your model is excelling---and where it isn't
• Working with a team on W&B means your colleagues can dig into and reproduce any of your experiments, collaborate on models, and seamlessly share insights with stakeholders

Weights & Biases Vendor Information
Vendor Overview
Think of W&B like GitHub for machine learning models. With a few lines of code, save everything you need to debug, compare and reproduce your models - architecture, hyperparameters, git commits, model weights, GPU usage, and even datasets and predictions.

W&B’s lightweight integrations work with any Python script, and you can sign up for a free account and start tracking and visualizing models in 5 minutes.

Used by top researchers including teams at Qualcomm, NVIDIA, OpenAI, Lyft, Pfizer, Toyota, Github, and MILA, W&B is part of the new standard of best practices for machine learning.
Vendor Details
Year Founded
2018
HQ Location
San Francisco, California, United States
Ownership
Private
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