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Download [FreeCoursesOnline.Me] PacktPub - Data Science Model Deployments and Cloud Computing on GCP

FreeCoursesOnline Me PacktPub Data Science Model Deployments and Cloud Computing on GCP

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[FreeCoursesOnline.Me] PacktPub - Data Science Model Deployments and Cloud Computing on GCP

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Total Size

1.8 GB

Total Files

82

Last Seen

2024-07-08 23:41

Hash

54C5ACD577FECD490F25350D1E2DEA673BE25C55

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/Chapter 1 Course Introduction and Prerequisites/

001. Course Introduction and Section Walkthrough.mp4

8.7 MB

002. Course Prerequisites.mp4

3.5 MB

/Chapter 10 Cloud Scheduler and Application Monitoring/

001. Introduction to Cloud Scheduler.mp4

3.8 MB

002. Lab - Cloud Scheduler in Action.mp4

20.8 MB

003. Lab - Set Up Alerting for Google App Engine Applications.mp4

35.9 MB

004. Lab - Set Up Alerting for Cloud-Run Applications.mp4

30.1 MB

005. Lab Assignment - Set Up Alerting for Cloud Function Applications.mp4

12.8 MB

/Chapter 2 Modern-Day Cloud Concepts/

001. Introduction.mp4

2.1 MB

002. Scalability - Horizontal Versus Vertical Scaling.mp4

16.1 MB

003. Serverless Versus Servers and Containerization.mp4

33.3 MB

004. Microservice Architecture.mp4

14.2 MB

005. Event-Driven Architecture.mp4

14.3 MB

/Chapter 3 Get Started with Google Cloud/

001. Set Up GCP Trial Account.mp4

15.9 MB

002. Google Cloud CLI Setup.mp4

19.3 MB

003. Get Comfortable with Basics of gcloud CLI.mp4

40.1 MB

004. gsutil and Bash Command Basics.mp4

39.0 MB

/Chapter 4 Cloud Run - Serverless and Containerized Applications/

001. Section Introduction.mp4

1.3 MB

002. Introduction to Dockers.mp4

8.9 MB

003. Lab - Install Docker Engine.mp4

16.1 MB

004. Lab - Run Docker Locally.mp4

24.8 MB

005. Lab - Run and Ship Applications Using the Container Registry.mp4

54.6 MB

006. Introduction to Cloud Run.mp4

3.8 MB

007. Lab - Deploy Python Application to Cloud Run.mp4

46.1 MB

008. Cloud Run Application Scalability Parameters.mp4

25.0 MB

009. Introduction to Cloud Build.mp4

7.0 MB

010. Lab - Python Application Deployment Using Cloud Build.mp4

40.0 MB

011. Lab - Continuous Deployment Using Cloud Build and GitHub.mp4

46.6 MB

/Chapter 5 Google App Engine - For Serverless Applications/

001. Introduction to App Engine.mp4

4.0 MB

002. App Engine - Different Environments.mp4

3.3 MB

003. Lab - Deploy Python Application to App Engine - Part 1.mp4

17.9 MB

004. Lab - Deploy Python Application to App Engine - Part 2.mp4

23.2 MB

005. Lab - Traffic Splitting in App Engine.mp4

14.9 MB

006. Lab - Deploy Python - BigQuery Application.mp4

27.9 MB

007. Caching and Its Use Cases.mp4

11.5 MB

008. Lab - Implement Caching Mechanism in Python Application - Part 1.mp4

45.8 MB

009. Lab - Implement Caching Mechanism in Python Application - Part 2.mp4

13.0 MB

010. Lab - Assignment Implement Caching.mp4

12.7 MB

011. Lab - Python App Deployment in a Flexible Environment.mp4

19.7 MB

012. Lab - Scalability and Instance Types in App Engine.mp4

38.7 MB

/Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/

001. Introduction.mp4

9.0 MB

002. Lab - Deploy Python Application Using Cloud Storage Triggers.mp4

54.8 MB

003. Lab - Deploy Python Application Using PubSub Triggers.mp4

17.7 MB

004. Lab - Deploy Python Application Using HTTP Triggers.mp4

15.7 MB

005. Introduction to Cloud Datastore.mp4

7.3 MB

006. Overview Product Wishlist Use Case.mp4

6.0 MB

007. Lab – Use Case Deployment - Part-1.mp4

47.2 MB

008. Lab – Use Case Deployment - Part-2.mp4

25.4 MB

/Chapter 7 Data Science Models with Google App Engine/

001. Introduction to ML Model Lifecycle.mp4

9.7 MB

002. Overview - Problem Statement.mp4

7.9 MB

003. Lab - Deploy Training Code to App Engine.mp4

53.9 MB

004. Lab - Deploy Model Serving Code to App Engine.mp4

27.9 MB

005. Overview - New Use Case.mp4

5.5 MB

006. Lab - Data Validation Using App Engine.mp4

39.9 MB

007. Lab - Workflow Template Introduction.mp4

27.7 MB

008. Lab - Final Solution Deployment Using Workflow and App Engine.mp4

63.0 MB

/Chapter 8 Dataproc Serverless PySpark/

001. Introduction.mp4

8.2 MB

002. PySpark Serverless Autoscaling Properties.mp4

7.2 MB

003. Persistent History Cluster.mp4

29.7 MB

004. Lab - Develop and Submit PySpark Job.mp4

37.0 MB

005. Lab - Monitoring and Spark UI.mp4

19.2 MB

006. Introduction to Airflow.mp4

15.8 MB

007. Lab - Airflow with Serverless PySpark.mp4

55.6 MB

008. Wrap Up.mp4

5.0 MB

/Chapter 9 Vertex AI - Machine Learning Framework/

001. Introduction.mp4

6.8 MB

002. Overview – Vertex AI UI.mp4

7.7 MB

003. Lab - Custom Model Training Using Web Console.mp4

59.7 MB

004. Lab - Custom Model Training Using SDK and Model Registries.mp4

43.5 MB

005. Lab - Model Endpoint Deployment.mp4

8.1 MB

006. Lab - Model Training Flow Using Python SDK.mp4

16.9 MB

007. Lab - Model Deployment Flow Using Python SDK.mp4

63.2 MB

008. Lab - Model Serving Using Endpoint with Python SDK.mp4

35.7 MB

009. Introduction to Kubeflow.mp4

13.5 MB

010. Lab - Code Walkthrough Using Kubeflow and Python.mp4

42.3 MB

011. Lab - Pipeline Execution in Kubeflow.mp4

31.6 MB

012. Lab - Final Pipeline Visualization Using Vertex UI and Walkthrough.mp4

11.7 MB

013. Lab - Add Model Evaluation Step in Kubeflow before Deployment.mp4

37.7 MB

014. Lab - Reusing Configuration Files for Pipeline Execution and Training.mp4

29.1 MB

015. Lab - Assignment Use Case - Fetch Data from BigQuery.mp4

7.6 MB

016. Wrap Up.mp4

6.5 MB

/

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Total files 82


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