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.
提供方
課程信息
對員工進行熱門技能培訓能否為您的公司帶來益處?
體驗 Coursera 企業版您將學到的內容有
Describe how to improve data quality and perform exploratory data analysis
Build and train AutoML Models using Vertex AI and BigQuery ML
Optimize and evaluate models using loss functions and performance metrics
Create repeatable and scalable training, evaluation, and test datasets
您將獲得的技能
- Tensorflow
- Bigquery
- Machine Learning
- Data Cleansing
對員工進行熱門技能培訓能否為您的公司帶來益處?
體驗 Coursera 企業版提供方
授課大綱 - 您將從這門課程中學到什麼
Introduction
Get to Know Your Data: Improve Data through Exploratory Data Analysis
Machine Learning in Practice
Training AutoML Models Using Vertex AI
BigQuery Machine Learning: Develop ML Models Where Your Data Lives
Optimization
Generalization and Sampling
Summary
審閱
- 5 stars69.41%
- 4 stars23.72%
- 3 stars5.01%
- 2 stars1.20%
- 1 star0.63%
來自LAUNCHING INTO MACHINE LEARNING的熱門評論
Very good course for beginners!
-1 star because I find labs to be less informational and practical and course to be more theoretical that practical!
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.
Very informative and well-prepared course, the only downside is, other than quizzes, there is no user input involved. Highly recommended nonetheless.
I highly recommend this course to learners who need an exposure on handling huge datasets using google big query SQL and data splitting strategies.
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