9781484260937 - machine learning in the oil and gas industry: including geosciences, reservoir engineering, and production engineering with python di pandey, yogendra narayan; rastogi, ayush; kainkaryam, sribharath; bhattacharya, srimoyee; saputelli, luigi (23 risultati)
Machine Learning in the Oil and Gas Industry : Including Geosciences, Reservoir Engineering, and Production Engineering With Python
Pandey, Yogendra Narayan; Rastogi, Ayush; Kainkaryam, Sribharath; Bhattacharya, Srimoyee; Saputelli, Luigi
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Machine Learning in the Oil and Gas Industry : Including Geosciences, Reservoir Engineering, and Production Engineering With Python
Pandey, Yogendra Narayan; Rastogi, Ayush; Kainkaryam, Sribharath; Bhattacharya, Srimoyee; Saputelli, Luigi
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Paperback or Softback. Condizione: New. Machine Learning in the Oil and Gas Industry: Including Geosciences, Reservoir Engineering, and Production Engineering with Python. Book.
Machine Learning in the Oil and Gas Industry: Including Geosciences, Reservoir Engineering, and Production Engineering with Python
Pandey, Yogendra Narayan; Rastogi, Ayush; Kainkaryam, Sribharath; Bhattacharya, Srimoyee; Saputelli, Luigi
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Paperback. Condizione: New. 1st ed. Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the different stages of industry operations. This leads to a survey…of some interesting problems, which are good candidates for applying machine and deep learning approaches. The initial chapters provide a primer on the Python programming language used for implementing the algorithms; this is followed by an overview of supervised and unsupervised machine learning concepts. The authors provide industry examples using open source data sets along with practical explanations of the algorithms, without diving too deep into the theoretical aspects of the algorithms employed. Machine Learning in the Oil and Gas Industry covers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and production engineering. Throughout the book, the emphasis is on providing a practical approach with step-by-step explanations and code examples for implementing machine and deep learning algorithms for solving real-life problems in the oil and gas industry. What You Will LearnUnderstanding the end-to-end industry life cycle and flow of data in the industrial operations of the oil and gas industryGet the basic concepts of computer programming and machine and deep learning required for implementing the algorithms usedStudy interesting industry problems that are good candidates for being solved by machine and deep learningDiscover the practical considerations and challenges for executing machine and deep learning projects in the oil and gas industry Who This Book Is For Professionals in the oil and gas industry who can benefit from a practical understanding of the machine and deep learning approach to solving real-life problems.
Machine Learning in the Oil and Gas Industry
Pandey, Yogendra Narayan; Rastogi, Ayush; Kainkaryam, Sribharath; Bhattacharya, Srimoyee; Saputelli, Luigi
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Condizione: New. pp. XX, 300 106 illus. 1st ed. edition NO-PA16APR2015-KAP.
Machine Learning in the Oil and Gas Industry
Pandey, Yogendra Narayan; Rastogi, Ayush; Kainkaryam, Sribharath; Bhattacharya, Srimoyee; Saputelli, Luigi
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Condizione: New. 2020. 1st ed. Paperback. . . . . .
Machine Learning in the Oil and Gas Industry : Including Geosciences, Reservoir Engineering, and Production Engineering With Python
Pandey, Yogendra Narayan; Rastogi, Ayush; Kainkaryam, Sribharath; Bhattacharya, Srimoyee; Saputelli, Luigi
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Machine Learning in the Oil and Gas Industry: Including Geosciences, Reservoir Engineering, and Production Engineering with Python
Pandey, Yogendra Narayan; Rastogi, Ayush; Kainkaryam, Sribharath; Bhattacharya, Srimoyee; Saputelli, Luigi
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Condizione: New. 2020. 1st ed. Paperback. . . . . . Books ship from the US and Ireland.
Machine Learning in the Oil and Gas Industry : Including Geosciences, Reservoir Engineering, and Production Engineering With Python
Pandey, Yogendra Narayan; Rastogi, Ayush; Kainkaryam, Sribharath; Bhattacharya, Srimoyee; Saputelli, Luigi
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Machine Learning in the Oil and Gas Industry | Including Geosciences, Reservoir Engineering, and Production Engineering with Python | Yogendra Narayan Pandey (u. a.) | Taschenbuch | xx | Englisch | 2020 | Apress | EAN 9781484260937 | Verantwortliche Person für die EU: APress in Springer Science + Bu…siness Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Paperback. Condizione: New. 1st ed. Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the different stages of industry operations. This leads to a survey…of some interesting problems, which are good candidates for applying machine and deep learning approaches. The initial chapters provide a primer on the Python programming language used for implementing the algorithms; this is followed by an overview of supervised and unsupervised machine learning concepts. The authors provide industry examples using open source data sets along with practical explanations of the algorithms, without diving too deep into the theoretical aspects of the algorithms employed. Machine Learning in the Oil and Gas Industry covers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and production engineering. Throughout the book, the emphasis is on providing a practical approach with step-by-step explanations and code examples for implementing machine and deep learning algorithms for solving real-life problems in the oil and gas industry. What You Will LearnUnderstanding the end-to-end industry life cycle and flow of data in the industrial operations of the oil and gas industryGet the basic concepts of computer programming and machine and deep learning required for implementing the algorithms usedStudy interesting industry problems that are good candidates for being solved by machine and deep learningDiscover the practical considerations and challenges for executing machine and deep learning projects in the oil and gas industry Who This Book Is For Professionals in the oil and gas industry who can benefit from a practical understanding of the machine and deep learning approach to solving real-life problems.
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Condizione: new. Questo è un articolo print on demand.
Machine Learning in the Oil and Gas Industry
Pandey, Yogendra Narayan; Rastogi, Ayush; Kainkaryam, Sribharath; Bhattacharya, Srimoyee; Saputelli, Luigi
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the d…ifferent stages of industry operations. This leads to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches. The initial chapters provide a primer on the Python programming language used for implementing the algorithms; this is followed by an overview of supervised and unsupervised machine learning concepts. The authors provide industry examples using open source data sets along with practical explanations of the algorithms, without diving too deep into the theoretical aspects of the algorithms employed. Machine Learning in the Oil and Gas Industry covers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and production engineering.Throughout the book, the emphasis is on providing a practical approach with step-by-step explanations and code examples for implementing machine and deep learning algorithms for solving real-life problems in the oil and gas industry.What You Will LearnUnderstanding the end-to-end industry life cycleand flow of data in the industrial operations of the oil and gas industry Get the basic concepts of computer programming and machine and deep learning required for implementing the algorithms used Study interesting industry problems that are good candidates for being solved by machine and deep learning Discover the practical considerations and challenges for executing machine and deep learning projects in the oil and gas industry Who This Book Is ForProfessionals in the oil and gas industry who can benefit from a practical understanding of the machine and deep learning approach to solving real-life problems. 320 pp. Englisch.
Machine Learning in the Oil and Gas Industry
Pandey, Yogendra Narayan; Rastogi, Ayush; Kainkaryam, Sribharath; Bhattacharya, Srimoyee; Saputelli, Luigi
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND pp. XX, 300 106 illus.
Machine Learning in the Oil and Gas Industry
Yogendra Narayan Pandey|Ayush Rastogi|Sribharath Kainkaryam|Srimoyee Bhattacharya|Luigi Saputelli
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Da: moluna, Greven, Germaniamoluna
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Contains real-life oil and gas company examples, based on data sets from those industriesCovers supervised and unsupervised learning Covers diverse industry topics, including geophysics, geological modeling, .
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the diffe…rent stages of industry operations. This leads to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches. The initial chapters provide a primer on the Python programming language used for implementing the algorithms; this is followed by an overview of supervised and unsupervised machine learning concepts. The authors provide industry examples using open source data sets along with practical explanations of the algorithms, without diving too deep into the theoretical aspects of the algorithms employed. Machine Learning in the Oil and Gas Industry covers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and production engineering.Throughout the book, the emphasis is on providing a practical approach with step-by-step explanations and code examples for implementing machine and deep learning algorithms for solving real-life problems in the oil and gas industry.What You Will LearnUnderstanding the end-to-end industry life cycle and flow of data in the industrial operations of the oil and gas industryGet the basic concepts of computer programming and machine and deep learning required for implementing the algorithms usedStudy interesting industry problems that are good candidates for being solved by machine and deep learningDiscover the practical considerations and challenges for executing machine and deep learning projects in the oil and gas industryWho This Book Is ForProfessionals in the oil and gas industry who can benefit from a practical understanding of the machine and deep learning approach to solving real-life problems.Libri GmbH, Europaallee 1, 36244 Bad Hersfeld 320 pp. Englisch.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the differ…ent stages of industry operations. This leads to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches. The initial chapters provide a primer on the Python programming language used for implementing the algorithms; this is followed by an overview of supervised and unsupervised machine learning concepts. The authors provide industry examples using open source data sets along with practical explanations of the algorithms, without diving too deep into the theoretical aspects of the algorithms employed. Machine Learning in the Oil and Gas Industry covers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and production engineering.Throughout the book, the emphasis is on providing a practical approach with step-by-step explanations and code examples for implementing machine and deep learning algorithms for solving real-life problems in the oil and gas industry.What You Will LearnUnderstanding the end-to-end industry life cycleand flow of data in the industrial operations of the oil and gas industry Get the basic concepts of computer programming and machine and deep learning required for implementing the algorithms used Study interesting industry problems that are good candidates for being solved by machine and deep learning Discover the practical considerations and challenges for executing machine and deep learning projects in the oil and gas industry Who This Book Is ForProfessionals in the oil and gas industry who can benefit from a practical understanding of the machine and deep learning approach to solving real-life problems.
