Data science and engineering at enterprise scale: notebook-driven results and analysis
As enterprise-scale data science sharpens its focus on data-driven decision making and machine learning, new tools have emerged to help facilitate these processes. This practical ebook shows data scientists and enterprise developers how the notebook interface, Apache Spark, and other collaboration t...
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| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Sebastopol, CA
O'Reilly Media
[2019]
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| Edition: | First edition. |
| Subjects: | |
| Links: | https://learning.oreilly.com/library/view/-/9781492039341/?ar |
| Summary: | As enterprise-scale data science sharpens its focus on data-driven decision making and machine learning, new tools have emerged to help facilitate these processes. This practical ebook shows data scientists and enterprise developers how the notebook interface, Apache Spark, and other collaboration tools are particularly well suited to bridge the communication gap between their teams. Through a series of real-world examples, author Jerome Nilmeier demonstrates how to generate a model that enables data scientists and developers to share ideas and project code. You'll learn how data scientists can approach real-world business problems with Spark and how developers can then implement the solution in a production environment. Dive deep into data science technologies, including Spark, TensorFlow, and the Jupyter Notebook Learn how Spark and Python notebooks enable data scientists and developers to work together Explore how the notebook environment works with Spark SQL for structured data Use notebooks and Spark as a launchpad to pursue supervised, unsupervised, and deep learning data models Learn additional Spark functionality, including graph analysis and streaming Explore the use of analytics in the production environment, particularly when creating data pipelines and deploying code. |
| Item Description: | Online resource; title from title page (Safari, viewed April 29, 2019) |
| Physical Description: | 1 Online-Ressource (1 volume) Illustrationen |
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| spelling | Nilmeier, Jerome VerfasserIn aut Data science and engineering at enterprise scale notebook-driven results and analysis Jerome Nilmeier First edition. Sebastopol, CA O'Reilly Media [2019] ©2019 1 Online-Ressource (1 volume) Illustrationen Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Online resource; title from title page (Safari, viewed April 29, 2019) As enterprise-scale data science sharpens its focus on data-driven decision making and machine learning, new tools have emerged to help facilitate these processes. This practical ebook shows data scientists and enterprise developers how the notebook interface, Apache Spark, and other collaboration tools are particularly well suited to bridge the communication gap between their teams. Through a series of real-world examples, author Jerome Nilmeier demonstrates how to generate a model that enables data scientists and developers to share ideas and project code. You'll learn how data scientists can approach real-world business problems with Spark and how developers can then implement the solution in a production environment. Dive deep into data science technologies, including Spark, TensorFlow, and the Jupyter Notebook Learn how Spark and Python notebooks enable data scientists and developers to work together Explore how the notebook environment works with Spark SQL for structured data Use notebooks and Spark as a launchpad to pursue supervised, unsupervised, and deep learning data models Learn additional Spark functionality, including graph analysis and streaming Explore the use of analytics in the production environment, particularly when creating data pipelines and deploying code. Information technology Management Machine learning Technologie de l'information ; Gestion Apprentissage automatique Information technology ; Management |
| spellingShingle | Nilmeier, Jerome Data science and engineering at enterprise scale notebook-driven results and analysis Information technology Management Machine learning Technologie de l'information ; Gestion Apprentissage automatique Information technology ; Management |
| title | Data science and engineering at enterprise scale notebook-driven results and analysis |
| title_auth | Data science and engineering at enterprise scale notebook-driven results and analysis |
| title_exact_search | Data science and engineering at enterprise scale notebook-driven results and analysis |
| title_full | Data science and engineering at enterprise scale notebook-driven results and analysis Jerome Nilmeier |
| title_fullStr | Data science and engineering at enterprise scale notebook-driven results and analysis Jerome Nilmeier |
| title_full_unstemmed | Data science and engineering at enterprise scale notebook-driven results and analysis Jerome Nilmeier |
| title_short | Data science and engineering at enterprise scale |
| title_sort | data science and engineering at enterprise scale notebook driven results and analysis |
| title_sub | notebook-driven results and analysis |
| topic | Information technology Management Machine learning Technologie de l'information ; Gestion Apprentissage automatique Information technology ; Management |
| topic_facet | Information technology Management Machine learning Technologie de l'information ; Gestion Apprentissage automatique Information technology ; Management |
| work_keys_str_mv | AT nilmeierjerome datascienceandengineeringatenterprisescalenotebookdrivenresultsandanalysis |