Launching into Machine Learning
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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.
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.
Author Name: Google Cloud
Author Description:
Google Cloud can help solve your toughest problems and grow your business. With Google Cloud, their infrastructure is your infrastructure. Their tools are your tools. And their innovations are your innovations.
Table of Contents
- Introduction
0mins - Introduction
0mins - Get to Know Your Data: Improve Data through Exploratory Data Analysis
56mins - Get to Know Your Data: Improve Data through Exploratory Data Analysis
52mins - Machine Learning in Practice
45mins - Machine Learning in Practice
45mins - Training AutoML Models Using Vertex AI
30mins - Training AutoML Models Using Vertex AI
30mins - BigQuery Machine Learning: Develop ML Models Where Your Data Lives
30mins - BigQuery Machine Learning: Develop ML Models Where Your Data Lives
30mins - Optimization
57mins - Optimization
57mins - Generalization and Sampling
28mins - Generalization and Sampling
28mins - Summary
0mins - Summary
0mins
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