LIVRAISON GARANTIE avant Noël pour vos achats avec Colissimo jusqu'au 20 décembre inclus sur tous les livres indiqués "Expédiés" sous 24h"
Tous nos rayons

Déjà client ? Identifiez-vous

Mot de passe oublié ?

Nouveau client ?

CRÉER VOTRE COMPTE
Data Science on the Google Cloud Platform: Implementing End-to-End Real-Time Data Pipelines: From In
Ajouter à une liste

Librairie Eyrolles - Paris 5e
Indisponible

Data Science on the Google Cloud Platform: Implementing End-to-End Real-Time Data Pipelines: From In

Data Science on the Google Cloud Platform: Implementing End-to-End Real-Time Data Pipelines: From In

Valliappa Lakshmanan

446 pages, parution le 07/04/2022

Résumé

This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. Throughout this updated second edition, you'll work through a sample business decision by employing a variety of data science approaches.Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. Throughout this updated second edition, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. You'll learn how to: Employ best practices in building highly scalable data and ML pipelines on Google Cloud Automate and schedule data ingest using Cloud Run Create and populate a dashboard in Data Studio Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery Conduct interactive data exploration with BigQuery Create a Bayesian model with Spark on Cloud Dataproc Forecast time series and do anomaly detection with BigQuery ML Aggregate within time windows with Dataflow Train explainable machine learning models with Vertex AI Operationalize ML with Vertex AI PipelinesValliappa (Lak) Lakshmanan is the director of analytics and AI solutions at Google Cloud, where he leads a team building cross-industry solutions to business problems. His mission is to democratize machine learning so that it can be done by anyone anywhere. Lak is the author or coauthor of Practical Machine Learning for Computer Vision, Machine Learning Design Patterns, Data Governance The Definitive Guide, Google BigQuery The Definitive Guide, and Data Science on the Google Cloud Platform.

Caractéristiques techniques

  PAPIER
Éditeur(s) O'Reilly
Auteur(s) Valliappa Lakshmanan
Parution 07/04/2022
Nb. de pages 446
EAN13 9781098118952

Avantages Eyrolles.com

Livraison à partir de 0,01 en France métropolitaine
Paiement en ligne SÉCURISÉ
Livraison dans le monde
Retour sous 15 jours
+ d'un million et demi de livres disponibles
satisfait ou remboursé
Satisfait ou remboursé
Paiement sécurisé
modes de paiement
Paiement à l'expédition
partout dans le monde
Livraison partout dans le monde
Service clients sav.client@eyrolles.com
librairie française
Librairie française depuis 1925
Recevez nos newsletters
Vous serez régulièrement informé(e) de toutes nos actualités.
Inscription