The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.
Introduction
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Skills You'll Learn
Tensorflow, Bigquery, Machine Learning, Data Cleansing
Reviews
4.6 (4,315 ratings)
- 5 stars69.43%
- 4 stars23.63%
- 3 stars5.05%
- 2 stars1.20%
- 1 star0.67%
PA
Aug 3, 2018
Good course, covering all the basics about machine learning and most importantly, everything that surrounds an ml project and you need to take into account to make your ml project successful.
KT
Apr 8, 2019
My favourite course in the specialisation. I think it's a great idea to use historic time-frame to explain the advances in ML and why there is so much hype around deep learning.
From the lesson
Machine Learning in Practice
In this module, we will introduce some of the main types of machine learning so that you can accelerate your growth as an ML practitioner.
Taught By
Google Cloud Training