Sprache: Englisch
Verlag: Cambridge University Press, 2023
ISBN 10: 1009201409 ISBN 13: 9781009201407
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Verlag: Cambridge University Press, 2023
ISBN 10: 1009201409 ISBN 13: 9781009201407
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Sprache: Englisch
Verlag: Cambridge University Press, 2023
ISBN 10: 1009201409 ISBN 13: 9781009201407
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Sprache: Englisch
Verlag: Cambridge University Press, 2023
ISBN 10: 1009201409 ISBN 13: 9781009201407
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Sprache: Englisch
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ISBN 10: 1009201409 ISBN 13: 9781009201407
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ISBN 10: 1009201409 ISBN 13: 9781009201407
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In den WarenkorbPaperback. Zustand: New. New. Data Science for the Geosciences provides students and instructors with the statistical and machine learning foundations to address Earth science questions using real-world case studies in natural hazards, climate change, environmental contamination and Earth resources. It focuses on techniques that address common characteristics of geoscientific data, including extremes, multivariate, compositional, geospatial and space-time methods. Step-by-step instructions are provided, enabling readers to easily follow the protocols for each method, solve their geoscientific problems and make interpretations. With an emphasis on intuitive reasoning throughout, students are encouraged to develop their understanding without the need for complex mathematics, making this the perfect text for those with limited mathematical or coding experience. Students can test their skills with homework exercises that focus on data scientific analysis, modeling, and prediction problems, and through the use of supplemental Python notebooks that can be applied to real datasets worldwide.
Sprache: Englisch
Verlag: Cambridge University Press, Cambridge, 2023
ISBN 10: 1009201409 ISBN 13: 9781009201407
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Paperback. Zustand: new. Paperback. Data Science for the Geosciences provides students and instructors with the statistical and machine learning foundations to address Earth science questions using real-world case studies in natural hazards, climate change, environmental contamination and Earth resources. It focuses on techniques that address common characteristics of geoscientific data, including extremes, multivariate, compositional, geospatial and space-time methods. Step-by-step instructions are provided, enabling readers to easily follow the protocols for each method, solve their geoscientific problems and make interpretations. With an emphasis on intuitive reasoning throughout, students are encouraged to develop their understanding without the need for complex mathematics, making this the perfect text for those with limited mathematical or coding experience. Students can test their skills with homework exercises that focus on data scientific analysis, modeling, and prediction problems, and through the use of supplemental Python notebooks that can be applied to real datasets worldwide. An accessible text that provides students and instructors with the data science foundations to address earth science questions using real-world case studies. Focusing on intuitive reasoning, students are encouraged to develop their understanding through exercises utilizing Python notebooks and real datasets. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Sprache: Englisch
Verlag: Cambridge University Press, 2023
ISBN 10: 1009201409 ISBN 13: 9781009201407
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Verlag: Cambridge University Press, 2023
ISBN 10: 1009201417 ISBN 13: 9781009201414
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ISBN 10: 1009201409 ISBN 13: 9781009201407
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Sprache: Englisch
Verlag: Cambridge University Press 2023-08-17, 2023
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Sprache: Englisch
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In den WarenkorbPaperback. Zustand: Brand New. 250 pages. 9.96x7.99x0.71 inches. In Stock.
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Verlag: Cambridge University Press, 2023
ISBN 10: 1009201409 ISBN 13: 9781009201407
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Paperback. Zustand: new. Paperback. Data Science for the Geosciences provides students and instructors with the statistical and machine learning foundations to address Earth science questions using real-world case studies in natural hazards, climate change, environmental contamination and Earth resources. It focuses on techniques that address common characteristics of geoscientific data, including extremes, multivariate, compositional, geospatial and space-time methods. Step-by-step instructions are provided, enabling readers to easily follow the protocols for each method, solve their geoscientific problems and make interpretations. With an emphasis on intuitive reasoning throughout, students are encouraged to develop their understanding without the need for complex mathematics, making this the perfect text for those with limited mathematical or coding experience. Students can test their skills with homework exercises that focus on data scientific analysis, modeling, and prediction problems, and through the use of supplemental Python notebooks that can be applied to real datasets worldwide. An accessible text that provides students and instructors with the data science foundations to address earth science questions using real-world case studies. Focusing on intuitive reasoning, students are encouraged to develop their understanding through exercises utilizing Python notebooks and real datasets. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Sprache: Englisch
Verlag: Cambridge University Press, GB, 2023
ISBN 10: 1009201409 ISBN 13: 9781009201407
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In den WarenkorbPaperback. Zustand: New. New. Data Science for the Geosciences provides students and instructors with the statistical and machine learning foundations to address Earth science questions using real-world case studies in natural hazards, climate change, environmental contamination and Earth resources. It focuses on techniques that address common characteristics of geoscientific data, including extremes, multivariate, compositional, geospatial and space-time methods. Step-by-step instructions are provided, enabling readers to easily follow the protocols for each method, solve their geoscientific problems and make interpretations. With an emphasis on intuitive reasoning throughout, students are encouraged to develop their understanding without the need for complex mathematics, making this the perfect text for those with limited mathematical or coding experience. Students can test their skills with homework exercises that focus on data scientific analysis, modeling, and prediction problems, and through the use of supplemental Python notebooks that can be applied to real datasets worldwide.
Sprache: Englisch
Verlag: Cambridge University Press, 2023
ISBN 10: 1009201417 ISBN 13: 9781009201414
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In den WarenkorbHardback. Zustand: New. Data Science for the Geosciences provides students and instructors with the statistical and machine learning foundations to address Earth science questions using real-world case studies in natural hazards, climate change, environmental contamination and Earth resources. It focuses on techniques that address common characteristics of geoscientific data, including extremes, multivariate, compositional, geospatial and space-time methods. Step-by-step instructions are provided, enabling readers to easily follow the protocols for each method, solve their geoscientific problems and make interpretations. With an emphasis on intuitive reasoning throughout, students are encouraged to develop their understanding without the need for complex mathematics, making this the perfect text for those with limited mathematical or coding experience. Students can test their skills with homework exercises that focus on data scientific analysis, modeling, and prediction problems, and through the use of supplemental Python notebooks that can be applied to real datasets worldwide.