TensorFlow Extended (TFX) is an end-to-end platform for deploying production ML pipelines.
This instructor-led, live training (online or onsite) is aimed at data scientists who wish to go from training a single ML model to deploying many ML models to production.
Introduction
Setting up TensorFlow Extended (TFX)
Overview of TFX Features and Architecture
Understanding Pipelines and Components
Working with TFX Components
Ingesting Data
Validating Data
Tranforming a Data Set
Analyzing a Model
Feature Engineering
Training a Model
Orchestrating a TFX Pipeline
Managing Meta Data for ML Pipelines
Model Versioning with TensorFlow Serving
Deploying a Model to Production
Troubleshooting
Summary and Conclusion
- An understanding of DevOps concepts
- Machine learning development experience
- Python programming experience
21 hours (usually 3 days including breaks)
