Data science on the Google cloud platform: implementing end-to-end real-time data pipelines: from ingest to machine learning
Lakshmanan, Valliappa
Data science on the Google cloud platform: implementing end-to-end real-time data pipelines: from ingest to machine learning - 2nd - New Delhi SPD: Shroff Publishers & Dist. Pvt. Ltd 2022 - xvii, 440p. : illustrations ; 24 cm
Making better decisions based on data -- Ingesting data into the cloud -- Creating compelling dashboards -- Streaming data: publication and
ingest -- Interactive data exploration -- Bayes classifier on cloud dataproc -- Machine learning: logistic regression on Spark -- Time-windowed
aggregate features -- Machine learning classifier using TensorFlow -- Real-time machine learning
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. Over 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 scien...
9789355422095
Google (Firm) Google Apps Real-time data processing Cloud computing Computing platformsData science
Google Apps Real-time data processing
Cloud computing
Computing platforms
004.33 LAK-D
Data science on the Google cloud platform: implementing end-to-end real-time data pipelines: from ingest to machine learning - 2nd - New Delhi SPD: Shroff Publishers & Dist. Pvt. Ltd 2022 - xvii, 440p. : illustrations ; 24 cm
Making better decisions based on data -- Ingesting data into the cloud -- Creating compelling dashboards -- Streaming data: publication and
ingest -- Interactive data exploration -- Bayes classifier on cloud dataproc -- Machine learning: logistic regression on Spark -- Time-windowed
aggregate features -- Machine learning classifier using TensorFlow -- Real-time machine learning
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. Over 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 scien...
9789355422095
Google (Firm) Google Apps Real-time data processing Cloud computing Computing platformsData science
Google Apps Real-time data processing
Cloud computing
Computing platforms
004.33 LAK-D