TensorFlow Extended (TFX) Training Course

Overview

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.

By the end of this training, participants will be able to:

• Install and configure TFX and supporting third-party tools.

• Use TFX to create and manage a complete ML production pipeline.

• Work with TFX components to carry out modeling, training, serving inference, and managing deployments.

• Deploy machine learning features to web applications, mobile applications, IoT devices and more.

Format Of The Course

• Interactive lecture and discussion.

• Lots of exercises and practice.

• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Course Outline

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

Requirements

• An understanding of DevOps concepts

• Machine learning development experience

• Python programming experience

Audience

• Data scientists

• ML engineers

• Operation engineers