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. 2021 Mar 11;121(8):4561–4677. doi: 10.1021/acs.chemrev.0c00752

Table 5. Overview of Popular Machine Learning Tools.

tool license programming language data set size development mode website
Weka open source Java small data sets GUI-based; many algorithms are already implemented https://www.cs.waikato.ac.nz/ml/weka/
DL4J open source Java larger data sets code-based https://deeplearning4j.org/
TensorFlow open source Python big data sets code-based https://www.tensorflow.org/
PyTorch open source Python big data sets code-based; many inbuilt algorithms https://pytorch.org/
R open source R big data sets code-based; many inbuilt algorithms https://www.r-project.org/
RapidMiner (similar to Weka) open source Java big data sets GUI-based https://rapidminer.com/
MATLAB closed source MATLAB; can interface with programs written in C++, Java, R, and Python medium sized data sets code-based; many inbuilt algorithms https://nl.mathworks.com/?s_tid=gn_logo
GNU Octave (alternative for MATLAB) open source Octave medium sized data sets code-based https://www.gnu.org/software/octave/