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packtpub data science model deployments cloud computing gcp video

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Lynda and other Courses >>> https://freecoursesonline.me/ Forum for discussion >>> https://onehack.us/ https://www.freecoursesonline.me/wp-content/uploads/2023/07/Data-Science.jpg PacktPub - Data Science Model Deployments and Cloud Computing on GCP [Video] [FCO] About this video Google Cloud platform is one of the most rapidly growing cloud providers in the market today, making it an essential skill for aspiring cloud engineers and data scientists. This comprehensive course covers all major serverless components on GCP, providing in-depth implementation of machine learning pipelines using Vertex AI with Kubeflow, and Serverless PySpark using Dataproc, App Engine, and Cloud Run. The course offers hands-on experience using GCP services such as Cloud Functions, Cloud Run, Google App Engine, and Vertex AI for custom model training and development, Kubeflow for workflow orchestration, and Dataproc Serverless for PySpark batch jobs. The course starts with modern-day cloud concepts, followed by GCP trial account setup and Google Cloud CLI setup. You will then look at Cloud Run for serverless and containerized applications, and Google App Engine for serverless applications. Next, you will study cloud functions for serverless and event-driven applications. After that, you will look at data science models with Google App Engine and Dataproc Serverless PySpark. Finally, you will explore Vertex AI for the machine learning framework, and cloud scheduler and application monitoring. By the end of the course, you will be confident in deploying and implementing applications at scale using Kubeflow, Spark, and serverless components on Google Cloud. Instructor(s) 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. General Info: Author(s): Siddharth Raghunath Language: English Released: May 2023 Videos Duration: 6h 55m ISBN: 9781805120438 Course Source: https://www./product/data-science-model-deployments-and-cloud-computing-on-gcp-video/9781805120438

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Chapter 1 Course Introduction and Prerequisites/001. Course Introduction and Section Walkthrough.mp4 8.3 MB
Chapter 1 Course Introduction and Prerequisites/002. Course Prerequisites.mp4 3.3 MB
Chapter 10 Cloud Scheduler and Application Monitoring/001. Introduction to Cloud Scheduler.mp4 3.6 MB
Chapter 10 Cloud Scheduler and Application Monitoring/002. Lab - Cloud Scheduler in Action.mp4 19.9 MB
Chapter 10 Cloud Scheduler and Application Monitoring/003. Lab - Set Up Alerting for Google App Engine Applications.mp4 34.3 MB
Chapter 10 Cloud Scheduler and Application Monitoring/004. Lab - Set Up Alerting for Cloud-Run Applications.mp4 28.7 MB
Chapter 10 Cloud Scheduler and Application Monitoring/005. Lab Assignment - Set Up Alerting for Cloud Function Applications.mp4 12.2 MB
Chapter 2 Modern-Day Cloud Concepts/001. Introduction.mp4 2.0 MB
Chapter 2 Modern-Day Cloud Concepts/002. Scalability - Horizontal Versus Vertical Scaling.mp4 15.3 MB
Chapter 2 Modern-Day Cloud Concepts/003. Serverless Versus Servers and Containerization.mp4 31.7 MB
Chapter 2 Modern-Day Cloud Concepts/004. Microservice Architecture.mp4 13.5 MB
Chapter 2 Modern-Day Cloud Concepts/005. Event-Driven Architecture.mp4 13.7 MB
Chapter 3 Get Started with Google Cloud/001. Set Up GCP Trial Account.mp4 15.2 MB
Chapter 3 Get Started with Google Cloud/002. Google Cloud CLI Setup.mp4 18.4 MB
Chapter 3 Get Started with Google Cloud/003. Get Comfortable with Basics of gcloud CLI.mp4 38.3 MB
Chapter 3 Get Started with Google Cloud/004. gsutil and Bash Command Basics.mp4 37.2 MB
Chapter 4 Cloud Run - Serverless and Containerized Applications/001. Section Introduction.mp4 1.3 MB
Chapter 4 Cloud Run - Serverless and Containerized Applications/002. Introduction to Dockers.mp4 8.5 MB
Chapter 4 Cloud Run - Serverless and Containerized Applications/003. Lab - Install Docker Engine.mp4 15.4 MB
Chapter 4 Cloud Run - Serverless and Containerized Applications/004. Lab - Run Docker Locally.mp4 23.7 MB
Chapter 4 Cloud Run - Serverless and Containerized Applications/005. Lab - Run and Ship Applications Using the Container Registry.mp4 52.0 MB
Chapter 4 Cloud Run - Serverless and Containerized Applications/006. Introduction to Cloud Run.mp4 3.6 MB
Chapter 4 Cloud Run - Serverless and Containerized Applications/007. Lab - Deploy Python Application to Cloud Run.mp4 44.0 MB
Chapter 4 Cloud Run - Serverless and Containerized Applications/008. Cloud Run Application Scalability Parameters.mp4 23.9 MB
Chapter 4 Cloud Run - Serverless and Containerized Applications/009. Introduction to Cloud Build.mp4 6.7 MB
Chapter 4 Cloud Run - Serverless and Containerized Applications/010. Lab - Python Application Deployment Using Cloud Build.mp4 38.1 MB
Chapter 4 Cloud Run - Serverless and Containerized Applications/011. Lab - Continuous Deployment Using Cloud Build and GitHub.mp4 44.4 MB
Chapter 5 Google App Engine - For Serverless Applications/001. Introduction to App Engine.mp4 3.8 MB
Chapter 5 Google App Engine - For Serverless Applications/002. App Engine - Different Environments.mp4 3.2 MB
Chapter 5 Google App Engine - For Serverless Applications/003. Lab - Deploy Python Application to App Engine - Part 1.mp4 17.1 MB
Chapter 5 Google App Engine - For Serverless Applications/004. Lab - Deploy Python Application to App Engine - Part 2.mp4 22.2 MB
Chapter 5 Google App Engine - For Serverless Applications/005. Lab - Traffic Splitting in App Engine.mp4 14.2 MB
Chapter 5 Google App Engine - For Serverless Applications/006. Lab - Deploy Python - BigQuery Application.mp4 26.6 MB
Chapter 5 Google App Engine - For Serverless Applications/007. Caching and Its Use Cases.mp4 10.9 MB
Chapter 5 Google App Engine - For Serverless Applications/008. Lab - Implement Caching Mechanism in Python Application - Part 1.mp4 43.7 MB
Chapter 5 Google App Engine - For Serverless Applications/009. Lab - Implement Caching Mechanism in Python Application - Part 2.mp4 12.4 MB
Chapter 5 Google App Engine - For Serverless Applications/010. Lab - Assignment Implement Caching.mp4 12.1 MB
Chapter 5 Google App Engine - For Serverless Applications/011. Lab - Python App Deployment in a Flexible Environment.mp4 18.8 MB
Chapter 5 Google App Engine - For Serverless Applications/012. Lab - Scalability and Instance Types in App Engine.mp4 36.9 MB
Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/001. Introduction.mp4 8.6 MB
Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/002. Lab - Deploy Python Application Using Cloud Storage Triggers.mp4 52.2 MB
Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/003. Lab - Deploy Python Application Using PubSub Triggers.mp4 16.9 MB
Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/004. Lab - Deploy Python Application Using HTTP Triggers.mp4 15.0 MB
Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/005. Introduction to Cloud Datastore.mp4 6.9 MB
Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/006. Overview Product Wishlist Use Case.mp4 5.7 MB
Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/007. Lab – Use Case Deployment - Part-1.mp4 45.0 MB
Chapter 6 Cloud Functions - Serverless and Event-Driven Applications/008. Lab – Use Case Deployment - Part-2.mp4 24.2 MB
Chapter 7 Data Science Models with Google App Engine/001. Introduction to ML Model Lifecycle.mp4 9.3 MB
Chapter 7 Data Science Models with Google App Engine/002. Overview - Problem Statement.mp4 7.5 MB
Chapter 7 Data Science Models with Google App Engine/003. Lab - Deploy Training Code to App Engine.mp4 51.4 MB
Chapter 7 Data Science Models with Google App Engine/004. Lab - Deploy Model Serving Code to App Engine.mp4 26.6 MB
Chapter 7 Data Science Models with Google App Engine/005. Overview - New Use Case.mp4 5.3 MB
Chapter 7 Data Science Models with Google App Engine/006. Lab - Data Validation Using App Engine.mp4 38.1 MB
Chapter 7 Data Science Models with Google App Engine/007. Lab - Workflow Template Introduction.mp4 26.4 MB
Chapter 7 Data Science Models with Google App Engine/008. Lab - Final Solution Deployment Using Workflow and App Engine.mp4 60.1 MB
Chapter 8 Dataproc Serverless PySpark/001. Introduction.mp4 7.9 MB
Chapter 8 Dataproc Serverless PySpark/002. PySpark Serverless Autoscaling Properties.mp4 6.8 MB
Chapter 8 Dataproc Serverless PySpark/003. Persistent History Cluster.mp4 28.3 MB
Chapter 8 Dataproc Serverless PySpark/004. Lab - Develop and Submit PySpark Job.mp4 35.3 MB
Chapter 8 Dataproc Serverless PySpark/005. Lab - Monitoring and Spark UI.mp4 18.4 MB
Chapter 8 Dataproc Serverless PySpark/006. Introduction to Airflow.mp4 15.1 MB
Chapter 8 Dataproc Serverless PySpark/007. Lab - Airflow with Serverless PySpark.mp4 53.1 MB
Chapter 8 Dataproc Serverless PySpark/008. Wrap Up.mp4 4.8 MB
Chapter 9 Vertex AI - Machine Learning Framework/001. Introduction.mp4 6.5 MB
Chapter 9 Vertex AI - Machine Learning Framework/002. Overview – Vertex AI UI.mp4 7.4 MB
Chapter 9 Vertex AI - Machine Learning Framework/003. Lab - Custom Model Training Using Web Console.mp4 56.9 MB
Chapter 9 Vertex AI - Machine Learning Framework/004. Lab - Custom Model Training Using SDK and Model Registries.mp4 41.5 MB
Chapter 9 Vertex AI - Machine Learning Framework/005. Lab - Model Endpoint Deployment.mp4 7.7 MB
Chapter 9 Vertex AI - Machine Learning Framework/006. Lab - Model Training Flow Using Python SDK.mp4 16.1 MB
Chapter 9 Vertex AI - Machine Learning Framework/007. Lab - Model Deployment Flow Using Python SDK.mp4 60.3 MB
Chapter 9 Vertex AI - Machine Learning Framework/008. Lab - Model Serving Using Endpoint with Python SDK.mp4 34.0 MB
Chapter 9 Vertex AI - Machine Learning Framework/009. Introduction to Kubeflow.mp4 12.9 MB
Chapter 9 Vertex AI - Machine Learning Framework/010. Lab - Code Walkthrough Using Kubeflow and Python.mp4 40.3 MB
Chapter 9 Vertex AI - Machine Learning Framework/011. Lab - Pipeline Execution in Kubeflow.mp4 30.2 MB
Chapter 9 Vertex AI - Machine Learning Framework/012. Lab - Final Pipeline Visualization Using Vertex UI and Walkthrough.mp4 11.2 MB
Chapter 9 Vertex AI - Machine Learning Framework/013. Lab - Add Model Evaluation Step in Kubeflow before Deployment.mp4 35.9 MB
Chapter 9 Vertex AI - Machine Learning Framework/014. Lab - Reusing Configuration Files for Pipeline Execution and Training.mp4 27.8 MB
Chapter 9 Vertex AI - Machine Learning Framework/015. Lab - Assignment Use Case - Fetch Data from BigQuery.mp4 7.2 MB
Chapter 9 Vertex AI - Machine Learning Framework/016. Wrap Up.mp4 6.2 MB
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Details for: PacktPub | Data Science Model Deployments and Cloud Computing on GCP [Video]

packtpub data science model deployments cloud computing gcp video