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种子名称： [FreeCoursesOnline.Me] PacktPub - Data Science Model Deployments and Cloud Computing on GCP
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文件数目： 79个文件
文件大小： 1.71 GB
收录时间： 2024-11-30 02:28
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资源热度： 10
最近下载： 2024-12-2 18:34

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

Chapter 1 Course Introduction and Prerequisites/001. Course Introduction and Section Walkthrough.mp48.34MB

Chapter 1 Course Introduction and Prerequisites/002. Course Prerequisites.mp43.29MB

Chapter 10 Cloud Scheduler and Application Monitoring/001. Introduction to Cloud Scheduler.mp43.63MB

Chapter 10 Cloud Scheduler and Application Monitoring/002. Lab - Cloud Scheduler in Action.mp419.88MB

Chapter 10 Cloud Scheduler and Application Monitoring/003. Lab - Set Up Alerting for Google App Engine Applications.mp434.26MB

Chapter 10 Cloud Scheduler and Application Monitoring/004. Lab - Set Up Alerting for Cloud-Run Applications.mp428.7MB

Chapter 10 Cloud Scheduler and Application Monitoring/005. Lab Assignment - Set Up Alerting for Cloud Function Applications.mp412.17MB

Chapter 2 Modern-Day Cloud Concepts/001. Introduction.mp42.02MB

Chapter 2 Modern-Day Cloud Concepts/002. Scalability - Horizontal Versus Vertical Scaling.mp415.32MB

Chapter 2 Modern-Day Cloud Concepts/003. Serverless Versus Servers and Containerization.mp431.72MB

Chapter 2 Modern-Day Cloud Concepts/004. Microservice Architecture.mp413.5MB

Chapter 2 Modern-Day Cloud Concepts/005. Event-Driven Architecture.mp413.66MB

Chapter 3 Get Started with Google Cloud/001. Set Up GCP Trial Account.mp415.16MB

Chapter 3 Get Started with Google Cloud/002. Google Cloud CLI Setup.mp418.37MB

Chapter 3 Get Started with Google Cloud/003. Get Comfortable with Basics of gcloud CLI.mp438.27MB

Chapter 3 Get Started with Google Cloud/004. gsutil and Bash Command Basics.mp437.21MB

Chapter 4 Cloud Run - Serverless and Containerized Applications/001. Section Introduction.mp41.26MB

Chapter 4 Cloud Run - Serverless and Containerized Applications/002. Introduction to Dockers.mp48.48MB

Chapter 4 Cloud Run - Serverless and Containerized Applications/003. Lab - Install Docker Engine.mp415.36MB

Chapter 4 Cloud Run - Serverless and Containerized Applications/004. Lab - Run Docker Locally.mp423.68MB

Chapter 4 Cloud Run - Serverless and Containerized Applications/005. Lab - Run and Ship Applications Using the Container Registry.mp452.03MB

Chapter 4 Cloud Run - Serverless and Containerized Applications/006. Introduction to Cloud Run.mp43.61MB

Chapter 4 Cloud Run - Serverless and Containerized Applications/007. Lab - Deploy Python Application to Cloud Run.mp443.96MB

Chapter 4 Cloud Run - Serverless and Containerized Applications/008. Cloud Run Application Scalability Parameters.mp423.88MB

Chapter 4 Cloud Run - Serverless and Containerized Applications/009. Introduction to Cloud Build.mp46.71MB

Chapter 4 Cloud Run - Serverless and Containerized Applications/010. Lab - Python Application Deployment Using Cloud Build.mp438.12MB

Chapter 4 Cloud Run - Serverless and Containerized Applications/011. Lab - Continuous Deployment Using Cloud Build and GitHub.mp444.42MB

Chapter 5 Google App Engine - For Serverless Applications/001. Introduction to App Engine.mp43.77MB

Chapter 5 Google App Engine - For Serverless Applications/002. App Engine - Different Environments.mp43.17MB

Chapter 5 Google App Engine - For Serverless Applications/003. Lab - Deploy Python Application to App Engine - Part 1.mp417.11MB

Chapter 5 Google App Engine - For Serverless Applications/004. Lab - Deploy Python Application to App Engine - Part 2.mp422.16MB

Chapter 5 Google App Engine - For Serverless Applications/005. Lab - Traffic Splitting in App Engine.mp414.18MB

Chapter 5 Google App Engine - For Serverless Applications/006. Lab - Deploy Python - BigQuery Application.mp426.62MB

Chapter 5 Google App Engine - For Serverless Applications/007. Caching and Its Use Cases.mp410.92MB

Chapter 5 Google App Engine - For Serverless Applications/008. Lab - Implement Caching Mechanism in Python Application - Part 1.mp443.71MB

Chapter 5 Google App Engine - For Serverless Applications/009. Lab - Implement Caching Mechanism in Python Application - Part 2.mp412.39MB

Chapter 5 Google App Engine - For Serverless Applications/010. Lab - Assignment Implement Caching.mp412.15MB

Chapter 5 Google App Engine - For Serverless Applications/011. Lab - Python App Deployment in a Flexible Environment.mp418.82MB

Chapter 5 Google App Engine - For Serverless Applications/012. Lab - Scalability and Instance Types in App Engine.mp436.94MB

Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/001. Introduction.mp48.56MB

Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/002. Lab - Deploy Python Application Using Cloud Storage Triggers.mp452.22MB

Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/003. Lab - Deploy Python Application Using PubSub Triggers.mp416.87MB

Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/004. Lab - Deploy Python Application Using HTTP Triggers.mp414.98MB

Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/005. Introduction to Cloud Datastore.mp46.92MB

Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/006. Overview Product Wishlist Use Case.mp45.74MB

Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/007. Lab – Use Case Deployment - Part-1.mp445.03MB

Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/008. Lab – Use Case Deployment - Part-2.mp424.18MB

Chapter 7 Data Science Models with Google App Engine/001. Introduction to ML Model Lifecycle.mp49.25MB

Chapter 7 Data Science Models with Google App Engine/002. Overview - Problem Statement.mp47.51MB

Chapter 7 Data Science Models with Google App Engine/003. Lab - Deploy Training Code to App Engine.mp451.43MB

Chapter 7 Data Science Models with Google App Engine/004. Lab - Deploy Model Serving Code to App Engine.mp426.64MB

Chapter 7 Data Science Models with Google App Engine/005. Overview - New Use Case.mp45.25MB

Chapter 7 Data Science Models with Google App Engine/006. Lab - Data Validation Using App Engine.mp438.05MB

Chapter 7 Data Science Models with Google App Engine/007. Lab - Workflow Template Introduction.mp426.37MB

Chapter 7 Data Science Models with Google App Engine/008. Lab - Final Solution Deployment Using Workflow and App Engine.mp460.07MB

Chapter 8 Dataproc Serverless PySpark/001. Introduction.mp47.86MB

Chapter 8 Dataproc Serverless PySpark/002. PySpark Serverless Autoscaling Properties.mp46.83MB

Chapter 8 Dataproc Serverless PySpark/003. Persistent History Cluster.mp428.33MB

Chapter 8 Dataproc Serverless PySpark/004. Lab - Develop and Submit PySpark Job.mp435.26MB

Chapter 8 Dataproc Serverless PySpark/005. Lab - Monitoring and Spark UI.mp418.35MB

Chapter 8 Dataproc Serverless PySpark/006. Introduction to Airflow.mp415.07MB

Chapter 8 Dataproc Serverless PySpark/007. Lab - Airflow with Serverless PySpark.mp453.06MB

Chapter 8 Dataproc Serverless PySpark/008. Wrap Up.mp44.8MB

Chapter 9 Vertex AI - Machine Learning Framework/001. Introduction.mp46.45MB

Chapter 9 Vertex AI - Machine Learning Framework/002. Overview – Vertex AI UI.mp47.35MB

Chapter 9 Vertex AI - Machine Learning Framework/003. Lab - Custom Model Training Using Web Console.mp456.92MB

Chapter 9 Vertex AI - Machine Learning Framework/004. Lab - Custom Model Training Using SDK and Model Registries.mp441.47MB

Chapter 9 Vertex AI - Machine Learning Framework/005. Lab - Model Endpoint Deployment.mp47.73MB

Chapter 9 Vertex AI - Machine Learning Framework/006. Lab - Model Training Flow Using Python SDK.mp416.08MB

Chapter 9 Vertex AI - Machine Learning Framework/007. Lab - Model Deployment Flow Using Python SDK.mp460.28MB

Chapter 9 Vertex AI - Machine Learning Framework/008. Lab - Model Serving Using Endpoint with Python SDK.mp434.03MB

Chapter 9 Vertex AI - Machine Learning Framework/009. Introduction to Kubeflow.mp412.89MB

Chapter 9 Vertex AI - Machine Learning Framework/010. Lab - Code Walkthrough Using Kubeflow and Python.mp440.29MB

Chapter 9 Vertex AI - Machine Learning Framework/011. Lab - Pipeline Execution in Kubeflow.mp430.17MB

Chapter 9 Vertex AI - Machine Learning Framework/012. Lab - Final Pipeline Visualization Using Vertex UI and Walkthrough.mp411.17MB

Chapter 9 Vertex AI - Machine Learning Framework/013. Lab - Add Model Evaluation Step in Kubeflow before Deployment.mp435.94MB

Chapter 9 Vertex AI - Machine Learning Framework/014. Lab - Reusing Configuration Files for Pipeline Execution and Training.mp427.78MB

Chapter 9 Vertex AI - Machine Learning Framework/015. Lab - Assignment Use Case - Fetch Data from BigQuery.mp47.23MB

Chapter 9 Vertex AI - Machine Learning Framework/016. Wrap Up.mp46.15MB