The Resource Data Science For Dummies, 2nd Edition, Pierson, Lillian
Data Science For Dummies, 2nd Edition, Pierson, Lillian
Resource Information
The item Data Science For Dummies, 2nd Edition, Pierson, Lillian represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Merrimack Valley Library Consortium.This item is available to borrow from 1 library branch.
Resource Information
The item Data Science For Dummies, 2nd Edition, Pierson, Lillian represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Merrimack Valley Library Consortium.
This item is available to borrow from 1 library branch.
- Summary
- Your ticket to breaking into the field of data science! Jobs in data science are projected to outpace the number of people with data science skills-making those with the knowledge to fill a data science position a hot commodity in the coming years. Data Science For Dummies is the perfect starting point for IT professionals and students interested in making sense of an organization's massive data sets and applying their findings to real-world business scenarios. From uncovering rich data sources to managing large amounts of data within hardware and software limitations, ensuring consistency in reporting, merging various data sources, and beyond, you'll develop the know-how you need to effectively interpret data and tell a story that can be understood by anyone in your organization. Provides a background in data science fundamentals and preparing your data for analysis Details different data visualization techniques that can be used to showcase and summarize your data Explains both supervised and unsupervised machine learning, including regression, model validation, and clustering techniques Includes coverage of big data processing tools like MapReduce, Hadoop, Dremel, Storm, and Spark It's a big, big data world out there-let Data Science For Dummies help you harness its power and gain a competitive edge for your organization
- Language
-
- eng
- eng
- Edition
- 2nd edition
- Extent
- 1 online resource (384 pages)
- Label
- Data Science For Dummies, 2nd Edition
- Title
- Data Science For Dummies, 2nd Edition
- Statement of responsibility
- Pierson, Lillian
- Language
-
- eng
- eng
- Summary
- Your ticket to breaking into the field of data science! Jobs in data science are projected to outpace the number of people with data science skills-making those with the knowledge to fill a data science position a hot commodity in the coming years. Data Science For Dummies is the perfect starting point for IT professionals and students interested in making sense of an organization's massive data sets and applying their findings to real-world business scenarios. From uncovering rich data sources to managing large amounts of data within hardware and software limitations, ensuring consistency in reporting, merging various data sources, and beyond, you'll develop the know-how you need to effectively interpret data and tell a story that can be understood by anyone in your organization. Provides a background in data science fundamentals and preparing your data for analysis Details different data visualization techniques that can be used to showcase and summarize your data Explains both supervised and unsupervised machine learning, including regression, model validation, and clustering techniques Includes coverage of big data processing tools like MapReduce, Hadoop, Dremel, Storm, and Spark It's a big, big data world out there-let Data Science For Dummies help you harness its power and gain a competitive edge for your organization
- http://library.link/vocab/creatorName
- Pierson, Lillian
- Nature of contents
- dictionaries
- http://library.link/vocab/relatedWorkOrContributorName
-
- Porway, Jake
- O'Reilly Media Company
- Label
- Data Science For Dummies, 2nd Edition, Pierson, Lillian
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Color
- multicolored
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Dimensions
- unknown
- Edition
- 2nd edition
- Extent
- 1 online resource (384 pages)
- Form of item
- online
- Issuing body
- Made available through: O'Reilly Media Company.
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Reproduction note
- Electronic reproduction.
- Specific material designation
- remote
- System control number
- (CaSebORM)9781119327639
- System details
- Mode of access: World Wide Web
- Label
- Data Science For Dummies, 2nd Edition, Pierson, Lillian
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Color
- multicolored
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Dimensions
- unknown
- Edition
- 2nd edition
- Extent
- 1 online resource (384 pages)
- Form of item
- online
- Issuing body
- Made available through: O'Reilly Media Company.
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Reproduction note
- Electronic reproduction.
- Specific material designation
- remote
- System control number
- (CaSebORM)9781119327639
- System details
- Mode of access: World Wide Web
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.mvlc.org/portal/Data-Science-For-Dummies-2nd-Edition-Pierson/P6XVG2m9cBM/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.mvlc.org/portal/Data-Science-For-Dummies-2nd-Edition-Pierson/P6XVG2m9cBM/">Data Science For Dummies, 2nd Edition, Pierson, Lillian</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.mvlc.org/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.mvlc.org/">Merrimack Valley Library Consortium</a></span></span></span></span></div>
