Software Alternatives, Accelerators & Startups

Numericcal VS Hopsworks

Compare Numericcal VS Hopsworks and see what are their differences

Numericcal logo Numericcal

Machine Learning Operationalization

Hopsworks logo Hopsworks

Machine learning (ML) application building platform
  • Numericcal Landing page
    Landing page //
    2023-05-15
  • Hopsworks Landing page
    Landing page //
    2023-08-19

Numericcal videos

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

+ Add video

Hopsworks videos

Hopsworks 3.0: Introduction to the new Python-centric Feature Store

More videos:

  • Review - End-to-end anomaly detection model using the Hopsworks platform
  • Review - Hopsworks Live Coding: Installing Hopsworks Open Source

Category Popularity

0-100% (relative to Numericcal and Hopsworks)
Data Science And Machine Learning
Data Science Notebooks
75 75%
25% 25
Machine Learning Tools
88 88%
12% 12
Monitoring Tools
0 0%
100% 100

User comments

Share your experience with using Numericcal and Hopsworks. For example, how are they different and which one is better?
Log in or Post with

What are some alternatives?

When comparing Numericcal and Hopsworks, 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.

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

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.

MCenter - Machine Learning Operationalization

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