Result: Data Science Toolkit: An all-in-one python library to help researchers and practitioners in implementing data science-related algorithms with less effort

Title:
Data Science Toolkit: An all-in-one python library to help researchers and practitioners in implementing data science-related algorithms with less effort
Authors:
El Hachimi, Chouaib, Belaqziz, Salwa, Khabba, Saïd, Chehbouni, Abdelghani
Contributors:
Université Mohammed VI Polytechnique = Mohammed VI Polytechnic University [Ben Guerir] (UM6P), Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Source:
Software Impacts. 12:100240-100240
Publisher Information:
CCSD; Elsevier, 2022.
Publication Year:
2022
Collection:
collection:INSU
collection:UNIV-TLSE3
collection:CNRS
collection:CNES
collection:OMP
collection:OMP-CESBIO
collection:INRAE
collection:INRAEOCCITANIETOULOUSE
collection:UNIV-UT3
collection:UT3-INP
collection:UT3-TOULOUSEINP
collection:RESEAU-EAU
Subject Terms:
BIG DATA, SUPPORT, Data representation, Data visualization, Data processing, Machine learning, Data science, [SDU]Sciences of the Universe [physics]
Original Identifier:
HAL: hal-04885922
Document Type:
Journal article<br />Journal articles
Language:
English
ISSN:
2665-9638
Relation:
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.simpa.2022.100240
DOI:
10.1016/j.simpa.2022.100240
Availability:
https://ut3-toulouseinp.hal.science/hal-04885922
Accession Number:
edshal.hal.04885922v1
Database:
HAL

Further Information

Data Science Toolkit (DST) is a python library built as a wrapper layer on top of several libraries to increase the abstraction level of the code, making its users more efficient and productive. The current version is widely used in our ongoing research activities that focus on optimizing agricultural management practices using artificial intelligence. DST adopts an object-oriented approach in implementing data science algorithms and is therefore composed of multiple classes such as the DataFrame class that adds additional functionalities to the standard pandas dataframe and the Model class that facilitates the building, training, and evaluation of machine learning models.