Introduction to Python in earth science data analysis: from descriptive statistics to machine learning

Introduction to Python in earth science data analysis: from descriptive statistics to machine learning

This textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences. It drives the reader from his very first steps with Python, like setting up the environment and starting writing the first lines of codes, to proficient use in visualizing, analyzing, and modelling data in the field of Earth Science. Each chapter contains explicative examples of code, and each script is commented in detail. The book is minded for very beginners in Python programming, and it can be used in teaching courses at master or PhD levels. Also, Early careers and experienced researchers who would like to start learning Python programming for the solution of geological problems will benefit the reading of the book.

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Bibliographic Details
Main Author: 1423211785557 Petrelli, M.
Format: Texto biblioteca
Language:eng
Published: Cham (Switzerland) Springer 2021
Subjects:earth sciences, data analysis, computer programs, machine learning, geology, SDGs, Goal 15 Life on land,
Online Access:https://link-springer-com.fao.idm.oclc.org/book/10.1007/978-3-030-78055-5
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spelling unfao:8572502023-03-01T15:20:12ZIntroduction to Python in earth science data analysis: from descriptive statistics to machine learning 1423211785557 Petrelli, M. textCham (Switzerland) Springer2021engThis textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences. It drives the reader from his very first steps with Python, like setting up the environment and starting writing the first lines of codes, to proficient use in visualizing, analyzing, and modelling data in the field of Earth Science. Each chapter contains explicative examples of code, and each script is commented in detail. The book is minded for very beginners in Python programming, and it can be used in teaching courses at master or PhD levels. Also, Early careers and experienced researchers who would like to start learning Python programming for the solution of geological problems will benefit the reading of the book.This textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences. It drives the reader from his very first steps with Python, like setting up the environment and starting writing the first lines of codes, to proficient use in visualizing, analyzing, and modelling data in the field of Earth Science. Each chapter contains explicative examples of code, and each script is commented in detail. The book is minded for very beginners in Python programming, and it can be used in teaching courses at master or PhD levels. Also, Early careers and experienced researchers who would like to start learning Python programming for the solution of geological problems will benefit the reading of the book.earth sciencesdata analysiscomputer programsmachine learninggeologySDGsGoal 15 Life on landhttps://link-springer-com.fao.idm.oclc.org/book/10.1007/978-3-030-78055-5URN:ISBN:978-3-030-78055-5
institution FAO IT
collection Koha
country Italia
countrycode IT
component Bibliográfico
access En linea
En linea
databasecode cat-fao-it
tag biblioteca
region Europa del Sur
libraryname David Lubin Memorial Library of FAO
language eng
topic earth sciences
data analysis
computer programs
machine learning
geology
SDGs
Goal 15 Life on land
earth sciences
data analysis
computer programs
machine learning
geology
SDGs
Goal 15 Life on land
spellingShingle earth sciences
data analysis
computer programs
machine learning
geology
SDGs
Goal 15 Life on land
earth sciences
data analysis
computer programs
machine learning
geology
SDGs
Goal 15 Life on land
1423211785557 Petrelli, M.
Introduction to Python in earth science data analysis: from descriptive statistics to machine learning
description This textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences. It drives the reader from his very first steps with Python, like setting up the environment and starting writing the first lines of codes, to proficient use in visualizing, analyzing, and modelling data in the field of Earth Science. Each chapter contains explicative examples of code, and each script is commented in detail. The book is minded for very beginners in Python programming, and it can be used in teaching courses at master or PhD levels. Also, Early careers and experienced researchers who would like to start learning Python programming for the solution of geological problems will benefit the reading of the book.
format Texto
topic_facet earth sciences
data analysis
computer programs
machine learning
geology
SDGs
Goal 15 Life on land
author 1423211785557 Petrelli, M.
author_facet 1423211785557 Petrelli, M.
author_sort 1423211785557 Petrelli, M.
title Introduction to Python in earth science data analysis: from descriptive statistics to machine learning
title_short Introduction to Python in earth science data analysis: from descriptive statistics to machine learning
title_full Introduction to Python in earth science data analysis: from descriptive statistics to machine learning
title_fullStr Introduction to Python in earth science data analysis: from descriptive statistics to machine learning
title_full_unstemmed Introduction to Python in earth science data analysis: from descriptive statistics to machine learning
title_sort introduction to python in earth science data analysis: from descriptive statistics to machine learning
publisher Cham (Switzerland) Springer
publishDate 2021
url https://link-springer-com.fao.idm.oclc.org/book/10.1007/978-3-030-78055-5
work_keys_str_mv AT 1423211785557petrellim introductiontopythoninearthsciencedataanalysisfromdescriptivestatisticstomachinelearning
_version_ 1768620559430582272

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