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Record Nr. |
UNINA9910459518403321 |
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Autore |
Robinson Michael F (Michael Frederick), <1966-> |
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Titolo |
The coldest crucible [[electronic resource] ] : Arctic exploration and American culture / / Michael F. Robinson |
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Pubbl/distr/stampa |
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Chicago, : University of Chicago Press, 2006 |
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ISBN |
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1-282-93289-6 |
9786612932892 |
0-226-72187-6 |
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Descrizione fisica |
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1 online resource (219 p.) |
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Disciplina |
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Soggetti |
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Explorers - United States - History - 19th century |
Scientists - United States - History - 19th century |
Science - United States - History - 19th century |
Electronic books. |
Arctic regions Discovery and exploration American |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references (p. 181-197) and index. |
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Nota di contenuto |
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Frontmatter -- Contents -- Illustrations -- Acknowledgments -- Introduction -- 1. Building an Arctic Tradition -- 2. A Man of Science and Humanity -- 3. An Arctic Divided -- 4. Dying Like Men -- 5. The New Machines -- 6. Savage Campaigns -- Conclusion -- Notes -- Bibliography -- Index |
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Sommario/riassunto |
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In the late 1800s, "Arctic Fever" swept across the nation as dozens of American expeditions sailed north to the Arctic to find a sea route to Asia and, ultimately, to stand at the North Pole. Few of these missions were successful, and many men lost their lives en route. Yet failure did little to dampen the enthusiasm of new explorers or the crowds at home that cheered them on. Arctic exploration, Michael F. Robinson argues, was an activity that unfolded in America as much as it did in the wintry hinterland. Paying particular attention to the perils facing explorers at home, The Coldest Crucible examines their struggles to build support for the expeditions before departure, defend their claims upon their return, and cast themselves as men worthy of the nation's full attention. In so doing, this book paints a new portrait of polar |
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voyagers, one that removes them from the icy backdrop of the Arctic and sets them within the tempests of American cultural life. With chronological chapters featuring emblematic Arctic explorers-including Elisha Kent Kane, Charles Hall, and Robert Peary-The Coldest Crucible reveals why the North Pole, a region so geographically removed from Americans, became an iconic destination for discovery. |
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2. |
Record Nr. |
UNINA9910632475203321 |
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Autore |
Mukhopadhyay Sayan |
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Titolo |
Advanced Data Analytics Using Python : With Architectural Patterns, Text and Image Classification, and Optimization Techniques / / by Sayan Mukhopadhyay, Pratip Samanta |
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Pubbl/distr/stampa |
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Berkeley, CA : , : Apress : , : Imprint : Apress, , 2023 |
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ISBN |
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Edizione |
[2nd ed. 2023.] |
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Descrizione fisica |
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1 online resource (259 pages) |
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Disciplina |
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Soggetti |
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Artificial intelligence - Data processing |
Machine learning |
Python (Computer program language) |
Artificial intelligence |
Data Science |
Machine Learning |
Python |
Artificial Intelligence |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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Chapter 1: Overview of Python Language -- Chapter 2: ETL with Python -- Chapter 3: Supervised Learning and Unsupervised Learning with Python -- Chapter 4: Clustering with Python -- Chapter 5: Deep Learning & Neural Networks -- Chapter 6: Time Series Analysis -- Chapter 7: Analytics in Scale. |
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Sommario/riassunto |
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Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language processing, and computer vision in the cloud environment. Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning. Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analytics withreinforcement learning. Finally, the recommender system in PySpark explains how to optimize models for a specific application. You will: Build intelligent systems for enterprise Review time series analysis, classifications, regression, and clustering Explore supervised learning, unsupervised learning, reinforcement learning, and transfer learning Use cloud platforms like GCP and AWS in data analytics Understand Covers design patterns in Python . |
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