Software Alternatives & Reviews

WEKA VS DimML

Compare WEKA VS DimML and see what are their differences

WEKA logo WEKA

WEKA is a set of powerful data mining tools that run on Java.

DimML logo DimML

The DimML programming language enables users to run any data solution on any website with only a single line of code.
  • WEKA Landing page
    Landing page //
    2018-09-29
  • DimML Landing page
    Landing page //
    2019-06-03

WEKA videos

Review of Feature Selection in Weka

More videos:

  • Review - Getting Started with Weka - Machine Learning Recipes #10
  • Tutorial - Data mining with Weka | Data mining Tutorial for Beginners

DimML videos

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Category Popularity

0-100% (relative to WEKA and DimML)
Data Science And Machine Learning
Data Science Tools
57 57%
43% 43
Python Tools
56 56%
44% 44
Data Dashboard
100 100%
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare WEKA and DimML

WEKA Reviews

15 data science tools to consider using in 2021
Weka is free software licensed under the GNU General Public License. It was developed at the University of Waikato in New Zealand starting in 1992; an initial version was rewritten in Java to create the current workbench, which was first released in 1999. Weka stands for the Waikato Environment for Knowledge Analysis and is also the name of a flightless bird native to New...

DimML Reviews

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What are some alternatives?

When comparing WEKA and DimML, you can also consider the following products

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

NumPy - NumPy is the fundamental package for scientific computing with Python

OpenCV - OpenCV is the world's biggest computer vision library

Dataiku - Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.

Exploratory - Exploratory enables users to understand data by transforming, visualizing, and applying advanced statistics and machine learning algorithms.