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MLPerf VS Managed MLflow

Compare MLPerf VS Managed MLflow and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

MLPerf logo MLPerf

Fair and useful benchmarks for measuring training and inference performance of ML hardware, software, and services.

Managed MLflow logo 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.
  • MLPerf Landing page
    Landing page //
    2023-08-18
  • Managed MLflow Landing page
    Landing page //
    2023-05-15

MLPerf videos

+ Add

SC22: AI Benchmarking & MLPerf™ Webinar

More videos:

  • Review - MLPerf & PyTorch | PyTorch Developer Day 2020
  • Review - Peter Mattson - MLPerf: Driving Innovation by Measuring Performance

Managed MLflow videos

No Managed MLflow videos yet. You could help us improve this page by suggesting one.

+ Add video

Category Popularity

0-100% (relative to MLPerf and Managed MLflow)

MLPerf

Managed MLflow

Data Science And Machine Learning
21 21%
Data Science And Machine Learning
79% 79
Data Science Notebooks
27 27%
Data Science Notebooks
73% 73
Machine Learning Tools
23 23%
Machine Learning Tools
77% 77
Predictive Analytics
100 100%
Predictive Analytics
0% 0

User comments

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What are some alternatives?

When comparing MLPerf and Managed MLflow, 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.

MCenter - Machine Learning Operationalization

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.

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

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

Spell - Deep Learning and AI accessible to everyone

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