- Course
- AI
- Cloud
Launching into Machine Learning
The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis.
What you'll learn
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.
Table of contents
- Introduction | 51s
- Improve data quality | 13m 6s
- Pluralsight: Getting Started with GCP and Qwiklabs | 3m 48s
- Lab intro: Improve the quality of your data | 1m 25s
- Lab Demo: Improve the quality of your data | 22m 38s
- Lab: Improving Data Quality | 10s
- What is exploratory data analysis | 4m 56s
- How is EDA used in machine learning | 4m 20s
- Data analysis and visualization | 3m 51s
- Lab intro: Explore the data using Python and BigQuery | 46s
- Lab: Exploratory Data Analysis Using Python and BigQuery | 10s
- Resources: Get to Know Your Data: Improve Data through Exploratory Data Analysis | 10s
About the author
Build, innovate, and scale with Google Cloud Platform.