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
Google 云端平台课程信息
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100% 在线
立即开始，按照自己的计划学习。
初级
完成时间大约为17 小时
英语（English）
字幕：英语（English）
您将学到的内容有
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
您将获得的技能
- Tensorflow
- Bigquery
- Machine Learning
- Data Cleansing
可灵活调整截止日期
根据您的日程表重置截止日期。
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
初级
完成时间大约为17 小时
英语（English）
字幕：英语（English）
提供方
Google 云端平台
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
授课大纲 - 您将从这门课程中学到什么
完成时间为 1 分钟
Introduction
This module provides an overview of the course and its objectives.
完成时间为 1 分钟
1 个视频 （总计 1 分钟）
完成时间为 4 小时
Get to Know Your Data: Improve Data through Exploratory Data Analysis
In this module, we look at how to improve the quality of our data and how to explore our data by performing exploratory data analysis. We look at the importance of tidy data in Machine Learning and show how it impacts data quality. For example, missing values can skew our results. You will also learn the importance of exploring your data. Once we have the data tidy, you will then perform exploratory data analysis on the dataset.
完成时间为 4 小时
9 个视频 （总计 57 分钟）, 1 个阅读材料, 3 个测验
完成时间为 3 小时
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.
完成时间为 3 小时
6 个视频 （总计 45 分钟）, 1 个阅读材料, 2 个测验
完成时间为 3 小时
Training AutoML Models Using Vertex AI
In this module, we will introduce training AutoML Models using Vertex AI.
完成时间为 3 小时
7 个视频 （总计 38 分钟）, 1 个阅读材料, 2 个测验
完成时间为 3 小时
BigQuery Machine Learning: Develop ML Models Where Your Data Lives
In this module, we will introduce BigQuery ML and its capabilities.
完成时间为 3 小时
8 个视频 （总计 30 分钟）, 1 个阅读材料, 3 个测验
完成时间为 1 小时
Optimization
In this module we will walk you through how to optimize your ML models.
完成时间为 1 小时
12 个视频 （总计 58 分钟）, 1 个阅读材料, 1 个测验
完成时间为 1 小时
Generalization and Sampling
Now it’s time to answer a rather weird question: when is the most accurate ML model not the right one to pick? As we hinted at in the last module on Optimization -- simply because a model has a loss metric of 0 for your training dataset does not mean it will perform well on new data in the real world. You will learn how to create repeatable training, evaluation, and test datasets and establish performance benchmarks.
完成时间为 1 小时
5 个视频 （总计 28 分钟）, 1 个阅读材料, 1 个测验
完成时间为 2 小时
Summary
This module is a summary of the Launching into Machine Learning course
完成时间为 2 小时
4 个阅读材料
审阅
- 5 stars69.34%
- 4 stars23.79%
- 3 stars5.01%
- 2 stars1.19%
- 1 star0.64%
来自LAUNCHING INTO MACHINE LEARNING的热门评论
由 AR 提供Aug 16, 2019
I got a whole idea on how to work on data from scratch. Model selection, generalization, splitting of data and performance metric were few things I learned from this course.
由 PT 提供Jun 25, 2018
Overall it was great, and very instructive. However, the Short History of ML was a little bit confusing with too many unexplained words and too many details too early.
由 AK 提供Aug 25, 2018
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!
由 SV 提供Dec 3, 2018
A great course to boost your confidence on practicing ML. It also teaches you some fresh skills like repeatable dataset partitioning techniques using just SQL.
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