Parametri
- 393pagine
- 14 ore di lettura
Maggiori informazioni sul libro
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
Acquisto del libro
Data Science on the Google Cloud Platform, Valliappa Lakshmanan
- Lingua
- Pubblicato
- 2019
- Rilegatura
- (In brossura),
- Condizioni del libro
- In buone condizioni
- Prezzo
- 9,39 €
Metodi di pagamento
Ancora nessuna valutazione.
- Titolo
- Data Science on the Google Cloud Platform
- Sottotitolo
- Implementing End-to-End Real-Time Data Pipelines - Updated for TensorFlow 2.0
- Lingua
- Inglese
- Autori
- Valliappa Lakshmanan
- Editore
- O'Reilly Media
- Pubblicato
- 2019
- Formato
- In brossura
- Pagine
- 393
- ISBN10
- 1491974567
- ISBN13
- 9781491974568
- Serie
- Tag
- Tecnologia, Letteratura specialistica, Intelligenza artificiale, Database, Analisi dei dati, Apprendimento Automatico, Google
- Descrizione
- 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