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Data Science on the Google Cloud Platform: Implementing End-To-End Real-Time...
by Lakshmanan, Valliappa | PB | Good
US $6.35
ApproximatelyC $8.57
Condition:
“Former library book; Pages can have notes/highlighting. Spine may show signs of wear. ~ ”... Read moreabout condition
Good
A book that has been read but is in good condition. Very minimal damage to the cover including scuff marks, but no holes or tears. The dust jacket for hard covers may not be included. Binding has minimal wear. The majority of pages are undamaged with minimal creasing or tearing, minimal pencil underlining of text, no highlighting of text, no writing in margins. No missing pages. See the seller’s listing for full details and description of any imperfections.
Out of Stock3 sold
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eBay item number:374870291216
Item specifics
- Condition
- Good
- Seller Notes
- Binding
- Paperback
- Weight
- 1 lbs
- Product Group
- Book
- IsTextBook
- No
- ISBN
- 1491974567
- Subject Area
- Computers
- Publication Name
- Data Science on the Google Cloud Platform : Implementing End-To-End Real-Time Data Pipelines: from Ingest to Machine Learning
- Publisher
- O'reilly Media, Incorporated
- Item Length
- 9.2 in
- Subject
- Systems Architecture / Distributed Systems & Computing, Data Modeling & Design, Data Processing, Databases / General
- Publication Year
- 2018
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Item Height
- 0.8 in
- Item Weight
- 24.1 Oz
- Item Width
- 7 in
- Number of Pages
- 402 Pages
About this product
Product Identifiers
Publisher
O'reilly Media, Incorporated
ISBN-10
1491974567
ISBN-13
9781491974568
eBay Product ID (ePID)
235117281
Product Key Features
Number of Pages
402 Pages
Publication Name
Data Science on the Google Cloud Platform : Implementing End-To-End Real-Time Data Pipelines: from Ingest to Machine Learning
Language
English
Publication Year
2018
Subject
Systems Architecture / Distributed Systems & Computing, Data Modeling & Design, Data Processing, Databases / General
Type
Textbook
Subject Area
Computers
Format
Trade Paperback
Dimensions
Item Height
0.8 in
Item Weight
24.1 Oz
Item Length
9.2 in
Item Width
7 in
Additional Product Features
Intended Audience
Trade
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
004.6782
Synopsis
Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). This hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of the book, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science. You'll learn how to: Automate and schedule data ingest, using an App Engine application Create and populate a dashboard in Google Data Studio Build a real-time analysis pipeline to carry out streaming analytics Conduct interactive data exploration with Google BigQuery Create a Bayesian model on a Cloud Dataproc cluster Build a logistic regression machine-learning model with Spark Compute time-aggregate features with a Cloud Dataflow pipeline Create a high-performing prediction model with TensorFlow Use your deployed model as a microservice you can access from both batch and real-time pipelines, Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). This hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of the book, you'??ll work through a sample business decision by employing a variety of data science approaches. Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science. You'??ll learn how to: Automate and schedule data ingest, using an App Engine application Create and populate a dashboard in Google Data Studio Build a real-time analysis pipeline to carry out streaming analytics Conduct interactive data exploration with Google BigQuery Create a Bayesian model on a Cloud Dataproc cluster Build a logistic regression machine-learning model with Spark Compute time-aggregate features with a Cloud Dataflow pipeline Create a high-performing prediction model with TensorFlow Use your deployed model as a microservice you can access from both batch and real-time pipelines
LC Classification Number
QA76.585
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Outstanding seller. Fair prices that are more than reasonable.. The product is in better condition than described, a true value for my money. Packaged and shipped well shows seller has concern for the products sold to arrive in excellent condition. The seller communicated timely with progress. Highly recommend this seller & will do business again. Thank you!
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