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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/launching-machine-learning
课程评论：没有评论
课程名称：机器学习入门 课程概述：该课程的开始部分讨论了数据的重要性，涵盖了如何提升数据质量及进行探索性数据分析。课程中介绍了Vertex AI AutoML的使用，讲解如何在无需编写代码的情况下构建、训练和部署机器学习模型。同时，您将了解BigQuery ML的优势。接着，我们将讨论如何优化机器学习模型，以及如何通过泛化和抽样来评估定制训练的模型质量。 课程大纲： 1. 模块一：实践中的机器学习 描述：在这一模块中，我们将介绍一些主要类型的机器学习，以加速您作为机器学习从业者的成长。 2. 模块二：BigQuery机器学习：在数据存储地点开发机器学习模型 描述：在这一模块中，我们将介绍BigQuery ML及其功能。 3. 模块三：总结 描述：这一模块对机器学习入门课程进行了总结。
Part: 1
Title:Machine Learning in Practice
Description: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.
Part: 2
Title:BigQuery Machine Learning: Develop ML Models Where Your Data Lives
Description:In this module, we will introduce BigQuery ML and its capabilities.
Part: 3
Title:Summary
Description:This module is a summary of the Launching into Machine Learning course
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.
