- Level Professional
- المدة 8 ساعات hours
- الطبع بواسطة Google Cloud
-
Offered by
عن
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.الوحدات
Introduction to Course
1
Videos
- Course introduction
Introduction to Vertex AI Feature Store: Module Introduction
1
Videos
- Introduction
Feature Store Benefits
1
Videos
- Feature Store benefits
Feature Store Terminology and Concepts
1
Videos
- Feature Store terminology and concepts
The Feature Store Data Model
1
Videos
- The Feature Store data model
Creating a Feature Store
1
Videos
- Creating a Feature Store
Serving Features: Batch and online
1
Assignment
- Introduction to Vertex AI Feature Store
1
Videos
- Serving features: Batch and online
1
Readings
- Resources: Introduction to Vertex AI Feature Store
Raw Data to Features: Module Introduction
1
Videos
- Introduction
Overview
2
Videos
- Overview of feature engineering
- Raw data to features
Feature attributes
5
Videos
- Good features versus bad features
- Features should be known at prediction-time
- Features should be numeric
- Features should have enough examples
- Bringing human insight
Representing Features
1
Assignment
- Raw Data to Features
1
Videos
- Representing features
1
Readings
- Resources: Raw Data to Features
Feature Engineering: Module Introduction
2
Videos
- Introduction
- Machine learning versus statistics
Feature Engineering in BigQuery ML
1
External Tool
- Lab: Performing Basic Feature Engineering in BigQuery ML
5
Videos
- Basic feature engineering
- Coursera: Getting Started with Google Cloud Platform and Qwiklabs
- Lab intro: Performing Basic Feature Engineering in BigQuery ML
- Advanced feature engineering: Feature crosses
- Bucketize and Transform Functions
Feature Engineering in Keras
1
Assignment
- Feature Engineering
2
External Tool
- Lab: Basic Feature Engineering in Keras
- Lab: Advanced Feature Engineering in Keras
5
Videos
- Predict housing prices
- Estimate taxi fare
- Temporal and geolocation features
- Lab intro: Basic Feature Engineering in Keras
- Lab intro: Advanced Feature Engineering in Keras
1
Readings
- Resources: Feature Engineering
Preprocessing and Feature Creation: Module Introduction
1
Videos
- Introduction
Apache Beam and Dataflow
1
Assignment
- Preprocessing and Feature Creation
2
Videos
- Apache Beam and Dataflow
- Dataflow terms and concepts
1
Readings
- Resources: Preprocessing and Feature Creation
Feature Crosses - TensorFlow Playground: Module Introduction
1
Videos
- Introduction
Feature Crosses
1
Assignment
- Feature Crosses - TensorFlow Playground
4
Videos
- What is a feature cross
- Discretization
- Lab intro: TensorFlow Playground: Use feature crosses to create a good classifier
- Lab intro: TensorFlow Playground: Too much of a good thing
1
Readings
- Resources: Feature Crosses - TensorFlow Playground
Introduction to TensorFlow Transform: Module Introduction
1
Videos
- Introduction
TensorFlow Transform
1
Assignment
- Introduction to TensorFlow Transform
4
Videos
- TensorFlow Transform
- Analyze phase
- Transform phase
- Supporting serving
1
Readings
- Resources: Introduction to TensorFlow Transform
Summary
4
Readings
- Summary
- Resource: All quiz questions
- Resource: All readings
- Resource: All slides
Auto Summary
Unlock the potential of your machine learning models with the "Feature Engineering" course, designed for data science and AI enthusiasts. Led by expert instructors on Coursera, this professional-level program delves into the advantages of utilizing Vertex AI Feature Store to enhance model accuracy. Throughout the course, you'll gain hands-on experience in identifying the most impactful data features and refining your feature engineering skills using powerful tools like BigQuery ML, Keras, and TensorFlow. With a comprehensive duration of 480 minutes, this course offers a thorough exploration of advanced techniques to elevate your data science projects. Ideal for professionals seeking to deepen their expertise, the course is available under the Starter subscription plan, providing accessible learning opportunities for those committed to advancing their machine learning proficiency. Join now to transform your approach to feature engineering and drive superior outcomes in your AI endeavors.

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