Want to know about Vertex AI Feature Store? Want to know how you can improve the accuracy of your ML models? What about how to find which data columns make the most useful features? Welcome to Feature Engineering, where we discuss good versus bad features and how you can preprocess and transform them for optimal use in your models. This course includes content and labs on feature engineering using BigQuery ML, Keras, and TensorFlow.
Introduction
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Reviews
4.5 (1,723 ratings)
- 5 stars63.37%
- 4 stars25.01%
- 3 stars7.42%
- 2 stars2.14%
- 1 star2.03%
BR
Jan 9, 2020
i really like the effort taken in developing this course, the structure. Kudos to Laks for converting lots of statistical and coding language to very simple understandable english.
TY
Sep 22, 2019
Feature engineering is important but less discussed compared to general ML or DNN. Feature cross is a new concept and yet very useful for dealing with large datasets.
From the lesson
Module 4: Preprocessing and Feature Creation
In this module you will learn more about Dataflow, which is a complementary technology to Apache Beam and both of them can help you build and run preprocessing and feature engineering.
Taught By
Google Cloud Training
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