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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Reseñas
4.5 (1,723 calificaciones)
- 5 stars63,37Â %
- 4 stars25,01Â %
- 3 stars7,42Â %
- 2 stars2,14Â %
- 1 star2,03Â %
BR
9 de ene. de 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
22 de sep. de 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.
De la lección
Module 3: Feature Engineering
This module reviews the differences between machine learning and statistics, and how to perform feature engineering in both BigQuery ML and Keras. We'll also cover some advanced feature engineering practices.
Impartido por:
Google Cloud Training
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