Data Science on the Google Cloud Platform: Implementing End-to-End Real-time Data Pipelines: from ingest to machine learning
| Author | : | |
| Rating | : | 4.82 (990 Votes) |
| Asin | : | 1491974567 |
| Format Type | : | paperback |
| Number of Pages | : | 250 Pages |
| Publish Date | : | 2016-03-08 |
| Language | : | English |
DESCRIPTION:
Valliappa (Lak) Lakshmanan is currently a Tech Lead for Data and Machine Learning Professional Services for Google Cloud. Before Google, he led a team of data scientists at the Climate Corporation and was a Research Scientist at NOAA National Severe Storms Laboratory, working on machine learning applications for severe weather diagnosis and prediction.. His mission is to democratize machine learning s
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). You’ll start with statistical methods, move into straightforward classification, and then explore windowing and real-time prediction.Move from basic to increasingly sophisticated methodsUnderstand interactive querying of very large datasets with BigQueryLearn about probabilistic decision making with SparkSQL and SparkTrain a TensorFlow model in Python and call it from JavaCreate a data processing pipeline with DataflowCompute time-windowed aggregates in real-time. With this practical guide, author and GCP Program Manager Valliappa Lakshmanan shows you how to gain insight into a sample business decision by applying different statistical and machine learning methods and tools.Along the
His mission is to democratize machine learning so that it can be done by anyone anywhere using Google's amazing infrastructure, without deep knowledge of statistics or programming or ownership of a lot of hardware. About the AuthorValliappa (Lak) Lakshmanan is currently a Tech Lead for Data and Machine Learning Professional Services for Google Cloud. Before Google, he led a team of data scientists at the Climate Corporation and was a Research Scientist at NOAA National Severe Storms Laboratory, working on machine learning applications for severe weather diagnosis and prediction.