Software Alternatives & Reviews

Activeloop VS Comet.ml

Compare Activeloop VS Comet.ml and see what are their differences

Activeloop logo Activeloop

Data lake for machine and deep learning. The fastest dataset management tool for computer vision.

Comet.ml logo Comet.ml

Comet lets you track code, experiments, and results on ML projects. It’s fast, simple, and free for open source projects.
  • Activeloop Landing page
    Landing page //
    2021-09-20

About

Activeloop provides an optimized format for unstructured data, so users can stream their machine learning datasets while training ML models in PyTorch and TensorFlow. Activeloop acts as a data lake for deep learning on unstructured data and offers in-browser dataset visualization, querying, and version control. On top of those features, Activeloop integrates with experimentation and labeling tools to allow rapid iteration on computer vision datasets.

Activeloop supports the following use cases:

Machine Learning teams can apply Activeloop's data infrastructure to ship their models fast in the following use cases:

  1. AgriTech
  2. Audio processing
  3. Autonomous Vehicles & Robotics
  4. Biomedical and Healthcare ML
  5. Multimedia: Image enhancement, video enhancement, face detection, sports analytics, or machine learning for AR/VR
  6. Safety & Security: surveillance machine learning with biometrics, facial recognition, or crowd counting
  • Comet.ml Landing page
    Landing page //
    2023-09-16

Activeloop

$ Details
$450.0 / Monthly (Growth Plan for up to 10 users)
Platforms
AWS GCP Python
Release Date
2019 July

Activeloop videos

Activeloop Product Demo Video

Comet.ml videos

Running Effective Machine Learning Teams: Common Issues, Challenges & Solutions | Comet.ml

More videos:

  • Review - Comet.ml - Supercharging Machine Learning

Category Popularity

0-100% (relative to Activeloop and Comet.ml)
Machine Learning Tools
38 38%
62% 62
Data Science And Machine Learning
Data Science Notebooks
17 17%
83% 83
Machine Learning
21 21%
79% 79

User comments

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Social recommendations and mentions

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

Activeloop mentions (4)

  • [P] I built a Chatbot to talk with any Github Repo. 🪄
    This repository contains two Python scripts that demonstrate how to create a chatbot using Streamlit, OpenAI GPT-3.5-turbo, and Activeloop's Deep Lake. The chatbot searches a dataset stored in Deep Lake to find relevant information and generates responses based on the user's input. Source: about 1 year ago
  • [D] NLP has HuggingFace, what does Computer Vision have?
    u/Remote_Cancel_7977 we just launched 100+ computer vision datasets via Activeloop Hub yesterday on r/ML (#1 post for the day!). Note: we do not intend to compete with HuggingFace (we're building the database for AI). Accessing computer vision datasets via Hub is much faster than via HuggingFace though, according to some third-party benchmarks. :). Source: about 2 years ago
  • [P] Database for AI: Visualize, version-control & explore image, video and audio datasets
    Hub, our open-source package, lets you stream datasets while training to PyTorch/TensorFlow. Check out how we achieved 95% GPU utilization while training on ImageNet at 50% less cost. We're building the Database for AI, with everything it should contain. If there's an adjacent feature that would make it more useful for your workflow, do let us know! Source: about 2 years ago
  • [P] Database for AI: Visualize, version-control & explore image, video and audio datasets
    I'm Davit from Activeloop (activeloop.ai). Source: about 2 years ago

Comet.ml mentions (0)

We have not tracked any mentions of Comet.ml yet. Tracking of Comet.ml recommendations started around Mar 2021.

What are some alternatives?

When comparing Activeloop and Comet.ml, you can also consider the following products

Iterative.ai - Iterative removes friction from managing datasets and ML models and introduces seamless data scientists collaboration.

neptune.ai - 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.

Pachyderm - Pachyderm is an open source analytics engine that uses Docker containers for distributed computations.

Weights & Biases - Developer tools for deep learning research

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.

DoltHub - DoltHub is where people collaboratively build, manage, and distribute structured data.