This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing. The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives.
Introduction
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Skills You'll Learn
Tensorflow, Machine Learning, Cloud Computing
Reviews
4.6 (1,448 ratings)
- 5 stars70.85%
- 4 stars22.65%
- 3 stars4.41%
- 2 stars0.89%
- 1 star1.17%
JW
May 29, 2018
This final course is also very good. Embedding is my favorite part and Lak is my favorite instructor.
Thanks Googlers! Looking forward to the next five courses.
SG
Sep 11, 2018
A lot of core neural network topics were presented in a productive way and I particularly liked the LAB showing how to write custom estimators.
From the lesson
Science of Machine Learning and Custom Training
This module reviews the art and science of machine learning and neural networks. We'll also discuss how to train custom ML models using Vertex AI.
Taught By
Google Cloud Training