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So far, dislib is highly focused on machine learning algorithms, and is greatly inspired by scikit-learn. However, other types of numerical algorithms might be added in the future. The main objective of dislib is to facilitate the execution of big data analytics algorithms in distributed platforms, such as clusters, clouds, and supercomputers.\n\nYou can find out more at:\n\n* https://dislib.bsc.es/en/stable/\n\n\n## Warnings and MN instructions\n\n**REMINDER**: For each language there **must** be **one** launch.sh and **one** clean.sh script\n          that executes the **stable** (base) version of that language. This script is used by\n          the automatic benchmarking process.\n\n**REMINDER**: For each version directory there **must** be a launcher script, a src directory with\nthe source code of that version, and a dist folder with the application binary or jar.\n\n\n**WARNING**: Addtional binaries commonly used by all versions **must** be placed in the\n         application's root folder.\n\n**WARNING**: Additional input data used by all versions **must** be placed in a new folder\n         inside the COMPSs_DATASETS with the **same** application name.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbsc-wdc%2Fapps","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbsc-wdc%2Fapps","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbsc-wdc%2Fapps/lists"}