Course
Skills Expanded
Feature Engineering
<p>This course explores the benefits of using Vertex AI Feature Store, how to improve the accuracy of ML models, and how to find which data columns make the most useful features. This course also includes content and labs on feature engineering using BigQuery ML, Keras, and TensorFlow.</p>
What you'll learn
This course explores the benefits of using Vertex AI Feature Store, how to improve the accuracy of ML models, and how to find which data columns make the most useful features. This course also includes content and labs on feature engineering using BigQuery ML, Keras, and TensorFlow.
Table of contents
Introduction
1min
Introduction
33mins
- Introduction 1m
- Feature Store benefits 5m
- Feature Store terminology and concepts 6m
- The Feature Store data model 1m
- Creating a Feature Store 10m
- Serving features: Batch and online 6m
- (Optional) Lab intro: Using Feature Store 0m
- Pluralsight: Getting Started with GCP and Qwiklabs 4m
- Lab: Using Feature Store 0m
- Resources: Introduction to Vertex AI Feature Store 0m
Introduction to Vertex AI Feature Store
33mins
- Introduction 1m
- Feature Store benefits 5m
- Feature Store terminology and concepts 6m
- The Feature Store data model 1m
- Creating a Feature Store 10m
- Serving features: Batch and online 6m
- (Optional) Lab intro: Using Feature Store 0m
- Pluralsight: Getting Started with GCP and Qwiklabs 4m
- Lab: Using Feature Store 0m
- Resources: Introduction to Vertex AI Feature Store 0m
Introduction to Vertex AI Feature Store
36mins
- Introduction 0m
- Machine learning versus statistics 3m
- Basic feature engineering 5m
- Lab intro: Performing Basic Feature Engineering in BigQuery ML 1m
- Lab: Performing Basic Feature Engineering in BQML 0m
- Advanced feature engineering: Feature crosses 6m
- Bucketize and Transform Functions 3m
- (Optional) Lab intro: Advanced Feature Engineering BigQuery ML 1m
- Lab: Performing Advanced Feature Engineering in BQML 0m
- Predict housing prices 7m
- Estimate taxi fare 3m
- Temporal and geolocation features 6m
- Lab intro: Basic Feature Engineering in Keras 1m
- Lab: Performing Basic Feature Engineering in Keras 0m
- Lab intro: Advanced Feature Engineering in Keras 0m
- Lab: Performing Advanced Feature Engineering in Keras 0m
- Resources: Feature Engineering 0m
Raw Data to Features
43mins
- Introduction 0m
- Overview of feature engineering 11m
- Raw data to features 2m
- Good features versus bad features 4m
- Features should be known at prediction-time 6m
- Features should be numeric 5m
- Features should have enough examples 6m
- Bringing human insight 0m
- Representing features 9m
- Resources: Raw Data to Features 0m
Raw Data to Features
4mins
Feature Engineering
36mins
- Introduction 0m
- Machine learning versus statistics 3m
- Basic feature engineering 5m
- Lab intro: Performing Basic Feature Engineering in BigQuery ML 1m
- Lab: Performing Basic Feature Engineering in BQML 0m
- Advanced feature engineering: Feature crosses 6m
- Bucketize and Transform Functions 3m
- (Optional) Lab intro: Advanced Feature Engineering BigQuery ML 1m
- Lab: Performing Advanced Feature Engineering in BQML 0m
- Predict housing prices 7m
- Estimate taxi fare 3m
- Temporal and geolocation features 6m
- Lab intro: Basic Feature Engineering in Keras 1m
- Lab: Performing Basic Feature Engineering in Keras 0m
- Lab intro: Advanced Feature Engineering in Keras 0m
- Lab: Performing Advanced Feature Engineering in Keras 0m
- Resources: Feature Engineering 0m
Feature Engineering
0mins
Preprocessing and Feature Creation
11mins
Preprocessing and Feature Creation
0mins
Feature Crosses - TensorFlow Playground
4mins
Feature Crosses - TensorFlow Playground
0mins
Introduction to TensorFlow Transform
20mins
Introduction to TensorFlow Transform
0mins
Summary
0mins
Summary
0mins
