Course
Skills Expanded
How Google Does Machine Learning
This course explores what ML is and what problems it can solve.
What you'll learn
This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models. The course discusses the five phases of converting a candidate use case to be driven by machine learning, and why it’s important to not skip them. The course ends with recognizing the biases that ML can amplify and how to recognize them.
Table of contents
Introduction to Course and Series
4mins
Introduction to Course and Series
36mins
- Introduction 1m
- What is ML? 9m
- What problems can it solve? 6m
- Activity intro: Framing a machine learning problem 2m
- Activity: Framing a machine learning problem 0m
- Activity solutions: Framing a machine learning problem 4m
- Infuse your apps with ML 4m
- Build a data strategy around ML 10m
- Resources: What It Means to Be AI First 0m
What It Means to be AI-First
36mins
- Introduction 1m
- What is ML? 9m
- What problems can it solve? 6m
- Activity intro: Framing a machine learning problem 2m
- Activity: Framing a machine learning problem 0m
- Activity solutions: Framing a machine learning problem 4m
- Infuse your apps with ML 4m
- Build a data strategy around ML 10m
- Resources: What It Means to Be AI First 0m
What It Means to be AI-First
40mins
- Introduction 1m
- Moving from experimentation to production 10m
- Components of Vertex AI 6m
- Pluralsight: Getting Started with GCP and Qwiklabs 4m
- Lab intro: Using an image dataset to train an AutoML model 0m
- Lab demo: Using an image dataset to train an AutoML model 7m
- Lab: Using an Image Dataset to Train an AutoML Model 0m
- Lab intro: Training an AutoML video classification model 0m
- Lab demo: Training an AutoML video classification model 9m
- Lab: Training an AutoML Video Classification Model 0m
- Tools to interact with Vertex AI 3m
- Resources: Machine Learning Development with Vertex AI 0m
How Google Does ML
31mins
How Google Does ML
11mins
Machine Learning Development with Vertex AI
40mins
- Introduction 1m
- Moving from experimentation to production 10m
- Components of Vertex AI 6m
- Pluralsight: Getting Started with GCP and Qwiklabs 4m
- Lab intro: Using an image dataset to train an AutoML model 0m
- Lab demo: Using an image dataset to train an AutoML model 7m
- Lab: Using an Image Dataset to Train an AutoML Model 0m
- Lab intro: Training an AutoML video classification model 0m
- Lab demo: Training an AutoML video classification model 9m
- Lab: Training an AutoML Video Classification Model 0m
- Tools to interact with Vertex AI 3m
- Resources: Machine Learning Development with Vertex AI 0m
Machine Learning Development with Vertex AI
0mins
Machine Learning Development with Vertex Notebooks
19mins
- Introduction 0m
- Machine learning development with Vertex Notebooks 5m
- (Optional) Lab intro: Vertex AI Model Builder SDK: Training and Making Predictions on an AutoML Model 1m
- (Optional) Lab demo: Vertex AI Model Builder SDK: Training and Making Predictions on an AutoML Model 13m
- Lab: Vertex AI Model Builder SDK: Training and Making Predictions on an AutoML Model 0m
- Resources: Machine Learning Development with Vertex Notebooks 0m
Machine Learning Development with Vertex Notebooks
0mins
Best Practices for Implementing Machine Learning on Vertex AI
11mins
Best Practices for Implementing Machine Learning on Vertex AI
0mins
Responsible AI Development
34mins
Responsible AI Development
0mins
Summary
0mins
Summary
0mins
