Software Alternatives & Reviews

MLPerf VS Numericcal

Compare MLPerf VS Numericcal and see what are their differences

MLPerf logo MLPerf

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

Numericcal logo Numericcal

Machine Learning Operationalization
  • MLPerf Landing page
    Landing page //
    2023-08-18
  • Numericcal Landing page
    Landing page //
    2023-05-15

MLPerf videos

SC22: AI Benchmarking & MLPerf™ Webinar

More videos:

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

Numericcal videos

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

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Category Popularity

0-100% (relative to MLPerf and Numericcal)
Data Science And Machine Learning
Data Science Notebooks
34 34%
66% 66
Machine Learning Tools
26 26%
74% 74
Predictive Analytics
100 100%
0% 0

User comments

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What are some alternatives?

When comparing MLPerf and Numericcal, 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

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

Spell - Deep Learning and AI accessible to everyone

Datatron - Datatron automates the deployment, monitoring, governance, and validation of your machine learning models in scikit-learn, TensorFlow, Keras, Pytorch, R, H20 and SAS

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.