TEACHING MACHINE LEARNING PROGRAMMING IN PANDAS AND JUPYTER-LAB - Gómez, Jorge;Hernández, Velssy
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This book is designed for those who wish to enter the world of machine learning, i.e. beginner mode. Initially, data manipulation through dataframes in the Python programming language, embedded in the Jupyter-lab and Pandas framework, will be addressed. Then data will be extracted from csv files to manage them in dataframes. Indexing, selection and allocation, indexing in Pandas, tag-based selection, conditional selection, data allocation, summary functions, maps and grouping and sorting. Finally, we will proceed to program basic supervised learning models such as linear regression with a…mehr

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Produktbeschreibung
This book is designed for those who wish to enter the world of machine learning, i.e. beginner mode. Initially, data manipulation through dataframes in the Python programming language, embedded in the Jupyter-lab and Pandas framework, will be addressed. Then data will be extracted from csv files to manage them in dataframes. Indexing, selection and allocation, indexing in Pandas, tag-based selection, conditional selection, data allocation, summary functions, maps and grouping and sorting. Finally, we will proceed to program basic supervised learning models such as linear regression with a single variable, linear regression with multiple variables, saving and loading the training model, data management with dummy variables, separation of the training and test data sets.
Autorenporträt
Ingeniero de Sistemas, Magister en Ingeniería Telemática en la Universidad del Cauca Colombia, PhD en Tecnologías de la Información y Comunicaciones de Universidad de Granada España, Docente tiempo completo del programa Ingeniería de Sistemas - Universidad de Córdoba, Miembro Rama IEEE.