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

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视频 2024-11-30 02:28 2024-12-22 03:54 49 1.71 GB 79
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FreeCoursesOnline Me PacktPub - Data Science Model Deployments and Cloud Computing on GCP

文件列表
  1. Chapter 1 Course Introduction and Prerequisites/001. Course Introduction and Section Walkthrough.mp48.34MB
  2. Chapter 1 Course Introduction and Prerequisites/002. Course Prerequisites.mp43.29MB
  3. Chapter 10 Cloud Scheduler and Application Monitoring/001. Introduction to Cloud Scheduler.mp43.63MB
  4. Chapter 10 Cloud Scheduler and Application Monitoring/002. Lab - Cloud Scheduler in Action.mp419.88MB
  5. Chapter 10 Cloud Scheduler and Application Monitoring/003. Lab - Set Up Alerting for Google App Engine Applications.mp434.26MB
  6. Chapter 10 Cloud Scheduler and Application Monitoring/004. Lab - Set Up Alerting for Cloud-Run Applications.mp428.7MB
  7. Chapter 10 Cloud Scheduler and Application Monitoring/005. Lab Assignment - Set Up Alerting for Cloud Function Applications.mp412.17MB
  8. Chapter 2 Modern-Day Cloud Concepts/001. Introduction.mp42.02MB
  9. Chapter 2 Modern-Day Cloud Concepts/002. Scalability - Horizontal Versus Vertical Scaling.mp415.32MB
  10. Chapter 2 Modern-Day Cloud Concepts/003. Serverless Versus Servers and Containerization.mp431.72MB
  11. Chapter 2 Modern-Day Cloud Concepts/004. Microservice Architecture.mp413.5MB
  12. Chapter 2 Modern-Day Cloud Concepts/005. Event-Driven Architecture.mp413.66MB
  13. Chapter 3 Get Started with Google Cloud/001. Set Up GCP Trial Account.mp415.16MB
  14. Chapter 3 Get Started with Google Cloud/002. Google Cloud CLI Setup.mp418.37MB
  15. Chapter 3 Get Started with Google Cloud/003. Get Comfortable with Basics of gcloud CLI.mp438.27MB
  16. Chapter 3 Get Started with Google Cloud/004. gsutil and Bash Command Basics.mp437.21MB
  17. Chapter 4 Cloud Run - Serverless and Containerized Applications/001. Section Introduction.mp41.26MB
  18. Chapter 4 Cloud Run - Serverless and Containerized Applications/002. Introduction to Dockers.mp48.48MB
  19. Chapter 4 Cloud Run - Serverless and Containerized Applications/003. Lab - Install Docker Engine.mp415.36MB
  20. Chapter 4 Cloud Run - Serverless and Containerized Applications/004. Lab - Run Docker Locally.mp423.68MB
  21. Chapter 4 Cloud Run - Serverless and Containerized Applications/005. Lab - Run and Ship Applications Using the Container Registry.mp452.03MB
  22. Chapter 4 Cloud Run - Serverless and Containerized Applications/006. Introduction to Cloud Run.mp43.61MB
  23. Chapter 4 Cloud Run - Serverless and Containerized Applications/007. Lab - Deploy Python Application to Cloud Run.mp443.96MB
  24. Chapter 4 Cloud Run - Serverless and Containerized Applications/008. Cloud Run Application Scalability Parameters.mp423.88MB
  25. Chapter 4 Cloud Run - Serverless and Containerized Applications/009. Introduction to Cloud Build.mp46.71MB
  26. Chapter 4 Cloud Run - Serverless and Containerized Applications/010. Lab - Python Application Deployment Using Cloud Build.mp438.12MB
  27. Chapter 4 Cloud Run - Serverless and Containerized Applications/011. Lab - Continuous Deployment Using Cloud Build and GitHub.mp444.42MB
  28. Chapter 5 Google App Engine - For Serverless Applications/001. Introduction to App Engine.mp43.77MB
  29. Chapter 5 Google App Engine - For Serverless Applications/002. App Engine - Different Environments.mp43.17MB
  30. Chapter 5 Google App Engine - For Serverless Applications/003. Lab - Deploy Python Application to App Engine - Part 1.mp417.11MB
  31. Chapter 5 Google App Engine - For Serverless Applications/004. Lab - Deploy Python Application to App Engine - Part 2.mp422.16MB
  32. Chapter 5 Google App Engine - For Serverless Applications/005. Lab - Traffic Splitting in App Engine.mp414.18MB
  33. Chapter 5 Google App Engine - For Serverless Applications/006. Lab - Deploy Python - BigQuery Application.mp426.62MB
  34. Chapter 5 Google App Engine - For Serverless Applications/007. Caching and Its Use Cases.mp410.92MB
  35. Chapter 5 Google App Engine - For Serverless Applications/008. Lab - Implement Caching Mechanism in Python Application - Part 1.mp443.71MB
  36. Chapter 5 Google App Engine - For Serverless Applications/009. Lab - Implement Caching Mechanism in Python Application - Part 2.mp412.39MB
  37. Chapter 5 Google App Engine - For Serverless Applications/010. Lab - Assignment Implement Caching.mp412.15MB
  38. Chapter 5 Google App Engine - For Serverless Applications/011. Lab - Python App Deployment in a Flexible Environment.mp418.82MB
  39. Chapter 5 Google App Engine - For Serverless Applications/012. Lab - Scalability and Instance Types in App Engine.mp436.94MB
  40. Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/001. Introduction.mp48.56MB
  41. Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/002. Lab - Deploy Python Application Using Cloud Storage Triggers.mp452.22MB
  42. Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/003. Lab - Deploy Python Application Using PubSub Triggers.mp416.87MB
  43. Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/004. Lab - Deploy Python Application Using HTTP Triggers.mp414.98MB
  44. Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/005. Introduction to Cloud Datastore.mp46.92MB
  45. Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/006. Overview Product Wishlist Use Case.mp45.74MB
  46. Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/007. Lab – Use Case Deployment - Part-1.mp445.03MB
  47. Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/008. Lab – Use Case Deployment - Part-2.mp424.18MB
  48. Chapter 7 Data Science Models with Google App Engine/001. Introduction to ML Model Lifecycle.mp49.25MB
  49. Chapter 7 Data Science Models with Google App Engine/002. Overview - Problem Statement.mp47.51MB
  50. Chapter 7 Data Science Models with Google App Engine/003. Lab - Deploy Training Code to App Engine.mp451.43MB
  51. Chapter 7 Data Science Models with Google App Engine/004. Lab - Deploy Model Serving Code to App Engine.mp426.64MB
  52. Chapter 7 Data Science Models with Google App Engine/005. Overview - New Use Case.mp45.25MB
  53. Chapter 7 Data Science Models with Google App Engine/006. Lab - Data Validation Using App Engine.mp438.05MB
  54. Chapter 7 Data Science Models with Google App Engine/007. Lab - Workflow Template Introduction.mp426.37MB
  55. Chapter 7 Data Science Models with Google App Engine/008. Lab - Final Solution Deployment Using Workflow and App Engine.mp460.07MB
  56. Chapter 8 Dataproc Serverless PySpark/001. Introduction.mp47.86MB
  57. Chapter 8 Dataproc Serverless PySpark/002. PySpark Serverless Autoscaling Properties.mp46.83MB
  58. Chapter 8 Dataproc Serverless PySpark/003. Persistent History Cluster.mp428.33MB
  59. Chapter 8 Dataproc Serverless PySpark/004. Lab - Develop and Submit PySpark Job.mp435.26MB
  60. Chapter 8 Dataproc Serverless PySpark/005. Lab - Monitoring and Spark UI.mp418.35MB
  61. Chapter 8 Dataproc Serverless PySpark/006. Introduction to Airflow.mp415.07MB
  62. Chapter 8 Dataproc Serverless PySpark/007. Lab - Airflow with Serverless PySpark.mp453.06MB
  63. Chapter 8 Dataproc Serverless PySpark/008. Wrap Up.mp44.8MB
  64. Chapter 9 Vertex AI - Machine Learning Framework/001. Introduction.mp46.45MB
  65. Chapter 9 Vertex AI - Machine Learning Framework/002. Overview – Vertex AI UI.mp47.35MB
  66. Chapter 9 Vertex AI - Machine Learning Framework/003. Lab - Custom Model Training Using Web Console.mp456.92MB
  67. Chapter 9 Vertex AI - Machine Learning Framework/004. Lab - Custom Model Training Using SDK and Model Registries.mp441.47MB
  68. Chapter 9 Vertex AI - Machine Learning Framework/005. Lab - Model Endpoint Deployment.mp47.73MB
  69. Chapter 9 Vertex AI - Machine Learning Framework/006. Lab - Model Training Flow Using Python SDK.mp416.08MB
  70. Chapter 9 Vertex AI - Machine Learning Framework/007. Lab - Model Deployment Flow Using Python SDK.mp460.28MB
  71. Chapter 9 Vertex AI - Machine Learning Framework/008. Lab - Model Serving Using Endpoint with Python SDK.mp434.03MB
  72. Chapter 9 Vertex AI - Machine Learning Framework/009. Introduction to Kubeflow.mp412.89MB
  73. Chapter 9 Vertex AI - Machine Learning Framework/010. Lab - Code Walkthrough Using Kubeflow and Python.mp440.29MB
  74. Chapter 9 Vertex AI - Machine Learning Framework/011. Lab - Pipeline Execution in Kubeflow.mp430.17MB
  75. Chapter 9 Vertex AI - Machine Learning Framework/012. Lab - Final Pipeline Visualization Using Vertex UI and Walkthrough.mp411.17MB
  76. Chapter 9 Vertex AI - Machine Learning Framework/013. Lab - Add Model Evaluation Step in Kubeflow before Deployment.mp435.94MB
  77. Chapter 9 Vertex AI - Machine Learning Framework/014. Lab - Reusing Configuration Files for Pipeline Execution and Training.mp427.78MB
  78. Chapter 9 Vertex AI - Machine Learning Framework/015. Lab - Assignment Use Case - Fetch Data from BigQuery.mp47.23MB
  79. Chapter 9 Vertex AI - Machine Learning Framework/016. Wrap Up.mp46.15MB
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