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Data Science Model Deployments and Cloud Computing on GCP

You're reading from   Data Science Model Deployments and Cloud Computing on GCP Learn to deploy and implement applications at scale using Kubeflow, Spark, and serverless components on Google Cloud

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Product type Video
Published in May 2023
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ISBN-13 9781805120438
Length 6hrs 55mins
Edition 1st Edition
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Author (1):
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Siddharth Raghunath Siddharth Raghunath
Author Profile Icon Siddharth Raghunath
Siddharth Raghunath
Siddharth Raghunath is a business-oriented engineering manager with a vast experience in the field of software development, distributed processing, and cloud data engineering. He has worked on different cloud platforms such as AWS and GCP as well as on-premise Hadoop clusters. He conducts seminars on distributed processing using Spark, real-time streaming and analytics, and best practices for ETL and data governance. He is passionate about coding and building optimal data pipelines for robust data processing and streaming solutions.
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Table of Contents (10) Chapters Close

1. Course Introduction and Prerequisites FREE CHAPTER 2. Modern-Day Cloud Concepts 3. Get Started with Google Cloud 4. Cloud Run - Serverless and Containerized Applications 5. Google App Engine - For Serverless Applications 6. Cloud Functions - Serverless and Event-Driven Applications 7. Data Science Models with Google App Engine 8. Dataproc Serverless PySpark 9. Vertex AI - Machine Learning Framework 10. Cloud Scheduler and Application Monitoring
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Data Science Model Deployments and Cloud Computing on GCP [Video]
Published in: May 2023
Publisher:
ISBN-13: 9781805120438
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Authors (1)

Profile icon Siddharth Raghunath
Siddharth Raghunath
Siddharth Raghunath is a business-oriented engineering manager with a vast experience in the field of software development, distributed processing, and cloud data engineering. He has worked on different cloud platforms such as AWS and GCP as well as on-premise Hadoop clusters. He conducts seminars on distributed processing using Spark, real-time streaming and analytics, and best practices for ETL and data governance. He is passionate about coding and building optimal data pipelines for robust data processing and streaming solutions.
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See other products by Siddharth Raghunath

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