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Google Cloud Professional Machine Learning Engineer Cert Prep: 4 Developing ML Models

Offered By: LinkedIn Learning

Tags

Machine Learning Courses TensorFlow Courses Microservices Courses Rust Courses Google App Engine Courses GitHub Actions Courses Transfer Learning Courses Hugging Face Courses

Course Description

Overview

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Learn about developing machine learning models in preparation for the Google Professional Machine Learning Engineer certification exam.

Syllabus

Introduction
  • Overview
  • Course four key terminology
1. Building Models
  • Using TensorFlow Playground
  • Overfitting vs. underfitting
  • Selecting the right metrics
2. Training Models
  • Training models with TensorFlow GPU-enabled Docker
  • Fine-tuning raw ingredients Hugging Face
  • Advantages transfer learning
3. Scaling Model Training and Serving
  • Operationalize microservices
  • Monitoring and logging with Rust on Google App Engine
  • Continuous integration Rust with GitHub Actions
  • Demo: Unit testing Rust
  • Demo: GitHub copilot-enabled Rust
  • Setup GCP workstation with Python
  • Demo: Google Cloud Shell
  • Demo: Google Cloud Editor
  • Demo: Google CLI SDK
  • Demo: Google gcloud CLI
  • Demo: Google App Engine Rust Deploy
  • Demo: Google App Engine Golang
Conclusion
  • Next steps

Taught by

Noah Gift

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