Скачать или смотреть Predict Bike Trip Duration with a Regression Model in BQML 2.5

Overview
BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.

BigQuery Machine Learning is a feature in BigQuery where data analysts can create, train, evaluate, and predict with machine learning models with minimal coding.

In this lab you will use the London bicycles dataset to build a regression model in BigQuery ML to predict trip duration. Let’s say that you're a bike rental business stocking two types of bicycles -- hardy commuter bikes and fast, but fragile, road bikes. If a bicycle rental is likely to be for a long duration, we need to have road bikes in stock, but if the rental is likely to be for a short duration, we need to have commuter bikes in stock. Therefore, in order to build a system to properly stock bicycles, we need to predict the duration of bicycle rentals.

Objectives
In this lab, you learn to perform the following tasks:
Query and explore the London bicycles dataset for feature engineering
Create a linear regression model in BigQuery ML
Evaluate the performance of your machine learning model
Extract your model weights
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