Launching into Machine Learning
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.
Introduction
Get to Know Your Data: Improve Data through Exploratory Data Analysis
Introduction
In this module we look at how to improve the quality of our data and how to explore our data by...
Improve data quality
In the course, you will learn that there are two phases in machine learning, a training phase a...
Lab Intro: Improve quality of your data
This lab focuses on improving data quality. Recall that machine learning models can only consum...
Lab demo: Improve quality of your data
Materials https://github.com/GoogleCloudPlatform/training-data-analyst
Lab: Improving Data Quality
Overview Machine learning models can only consume numeric data, and that numeric data should be ...
What are exploratory data analysis
In statistics, exploratory data analysis or EDA is an approach to analyzing data sets to summar...
How is EDA used in machine learning
How is EDA used in machine learning? As we mentioned, the exploratory data analysis approach do...
Data analysis and visualization
The purpose of an EDA is to find insights which will serve for data cleaning, preparation, or t...
Lab intro: Explore the data using Python and BigQuery
In this lab, you will perform exploratory data analysis on the U.S.A housing data set and the N...
Lab: Exploratory Data Analysis Using Python and BigQuery
Overview This lab is in introduction to linear regression using Python and Scikit-Learn. This la...
Quiz: Get to know your data: Improve data through Exploratory Data Analysis
1. Which of the following is not a component of Exploratory Data Analysis? A. Statistical Analys...
References
Module 1: Get to Know Your Data: Improve Data through Exploratory Data Analysis Guide to Data Qu...