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- Level: Advanced
- Duration: 03h 04m 57s
- Release date: 2021-02-18
- Author: Google Cloud
- Provider: Pluralsight
ML Pipelines on Google Cloud
Description
Content
In this course, you will be learning from ML Engineers and Trainers who work with the state-of-the-art development of ML pipelines here at Google Cloud. The first few modules will cover about TensorFlow Extended (or TFX).
- Introduction03m
- Course Introduction03m
- [Important] - Please Read00m
- Introduction to TFX Pipelines48m
- TensorFlow Extended (TFX)07m
- TFX concepts09m
- TFX standard data components10m
- TFX standard model components10m
- TFX pipeline nodes02m
- TFX libraries06m
- Lab Intro: TFX Walkthrough00m
- Getting Started With GCP And Qwiklabs04m
- Lab: TFX Standard Components Walkthrough00m
- Pipeline orchestration with TFX24m
- TFX Orchestrators08m
- Apache Beam07m
- TFX on Cloud AI Platform05m
- Lab Intro : TFX on Cloud AI Platform04m
- Lab: TFX on Cloud AI Platform Pipelines00m
- Custom components and CI/CD for TFX pipelines25m
- TFX custom components : Python functions04m
- TFX custom components : containers + subclassed07m
- CI/CD for TFX pipeline workflows12m
- Lab Intro: CI/CD lab walkthrough02m
- Lab: CI/CD for a TFX pipeline00m
- ML Metadata with TFX09m
- TFX Pipeline Metadata05m
- TFX ML Metadata data model04m
- Lab Intro: TFX Pipeline Metadata00m
- Lab: TFX Metadata00m
- Continuous Training with multiple SDKs, KubeFlow & AI Platform Pipelines08m
- Containerized Training Applications03m
- Containerizing PyTorch, Scikit, and XGBoost Applications01m
- KubeFlow & AI Platform Pipelines02m
- Continuous Training02m
- Lab Intro : Continuous Training with multiple SDKs00m
- Lab: Continuous Training with TensorFlow, PyTorch, XGBoost, and Scikit Learn Models with Kubeflow and AI Platform Pipelines00m
- Continuous Training with Cloud Composer26m
- What is Cloud Composer?06m
- Core Concepts of Apache Airflow09m
- Continuous Training Pipelines using Cloud Composer (data)06m
- Continuous Training Pipelines using Cloud Composer (model)04m
- Apache Airflow, Containers, and TFX01m
- Lab Intro : Continuous Training Pipelines with Cloud Composer00m
- Lab: Continuous Training Pipelines with Cloud Composer00m
- ML Pipelines with MLflow37m
- Introduction01m
- Overview of ML development challenges05m
- How MLflow tackles these challenges03m
- MLflow tracking07m
- MLflow projects05m
- MLflow models07m
- MLflow model registry04m
- Demo : Introduction00m
- Deploying MLflow Locally Tracking Keras, TensorFlow, and Sckit-learn experiments05m
- Summary01m
- Course Summary01m
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