08
Feature Engineering
08
Feature Engineering
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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.
Course Info
Objectives
- Describe Vertex AI Feature Store and compare the key required aspects of a good feature.
- Perform feature engineering using BigQuery ML, Keras, and TensorFlow.
- Discuss how to preprocess and explore features with Dataflow and Dataprep.
- Use tf.Transform.
Prerequisites
Familiarity with Python or other programming languages.
Audience
- Data Analysts
- Data Engineers
- Data Scientists
- ML Engineers
- ML Software Engineers
Available languages
English, español (Latinoamérica), français, 日本語, 한국어, português (Brasil), and italiano
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After finishing this course, you can explore additional content in your learning path or browse the catalog.
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Interested in taking this course with one of our authorized on-demand partners?
Explore Google Cloud content on Coursera and Pluralsight.
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View the public classroom schedule here.
Can I take this course for free?
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