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Weights & Biases VS

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Developer tools for deep learning research

Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.
Weights & Biases Landing Page
Weights & Biases Landing Page Landing Page Landing Page

Track and version your notebooks Log all your notebooks directly from Jupyter or Jupyter Lab. All you need is to install a Jupyter extension.

Manage your experimentation process Neptune tracks your work with virtually no interference to the way you like to do it. Decide what is relevant to your project and start tracking: - Metrics - Hyperparameters - Data versions - Model files - Images - Source code

Integrate with your workflow easily Neptune is a lightweight extension to your current workflow. Works with all common technologies in data science domain and integrates with other tools. It will take you 5 minutes to get started.

Weights & Biases details

Data Science And Machine Learning Data Science Notebooks Machine Learning Tools
Pricing URL-
Details $-
Release Date- details

Data Science And Machine Learning Data Science Notebooks Machine Learning Tools Machine Learning
Pricing URL Official Pricing  
Details $freemium
Release Date2018-04-03

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Machine Learning Experiment Management with - How to start

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  1. Easy to use, not overdone, good for model management and collab

    Only negative is I didn't see it integrated with Azure, does with Google, AWS and one more. Looks real nice, and pretty powerful and plenty useful features for a data science group

Social recommendations and mentions

Based on our record, seems to be more popular. It has been mentiond 4 times since March 2021. We are tracking product recommendations and mentions on Reddit, HackerNews and some other platforms. They can help you identify which product is more popular and what people think of it.

Weights & Biases mentions (0)

We have not tracked any mentions of Weights & Biases yet. Tracking of Weights & Biases recommendations started around Mar 2021. mentions (4)

  • Taking on the ML pipeline challenge: why data scientists need to own their ML workflows in production
    So, if you even want to use MLFlow to track your experiments, run the pipeline on Airflow, and then deploy a model to a Neptune Model Registry, ZenML will facilitate this MLOps Stack for you. This decision can be made jointly by the data scientists and engineers. As ZenML is a framework, custom pieces of the puzzle can also be added here to accommodate legacy infrastructure. - Source: / about 2 months ago
  • [D] Alternatives to W&B?
    There are a lot of other tools:, comet_ml, mlflow, etc. - Source: Reddit / 7 months ago
  • Multivariant Time Series Forecasting with LSTM - course advice
    Optimizing the model with e.g., TensorBoard or NepTune. - Source: Reddit / 7 months ago
  • Data science experiments management with Weights & Biases platform
    Neptune is a lightweight run management tool that helps you keep track of your machine learning runs. It offers 3 types of subscriptions, 2 of which are paid. If you are going to use this service individually, then you will get free access. - Source: Reddit / 9 months ago

What are some alternatives?

When comparing Weights & Biases and, you can also consider the following products

Algorithmia - Algorithmia makes applications smarter, by building a community around algorithm development, where state of the art algorithms are always live and accessible to anyone.

Spell - Deep Learning and AI accessible to everyone

Managed MLflow - Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete Machine Learning lifecycle with enterprise reliability, security, and scale. - Comet lets you track code, experiments, and results on ML projects. It’s fast, simple, and free for open source projects.

5Analytics - The 5Analytics AI platform enables you to use artificial intelligence to automate important commercial decisions and implement digital business models.

MCenter - Machine Learning Operationalization

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