Create ML Models with BigQuery ML: Challenge Lab recensioni

Halimathu S. · Recensione inserita circa un anno fa

Bhagyashree P. · Recensione inserita circa un anno fa

Aman N. · Recensione inserita circa un anno fa

Camille H. · Recensione inserita circa un anno fa

Zhenru C. · Recensione inserita circa un anno fa

Zhenru C. · Recensione inserita circa un anno fa

Жандос О. · Recensione inserita circa un anno fa

Octavia R. · Recensione inserita circa un anno fa

Task 3 doesn't work

Pierpaolo S. · Recensione inserita circa un anno fa

Md I. · Recensione inserita circa un anno fa

Ozana I. · Recensione inserita circa un anno fa

I finished Task 3 by creating and evaluating the new model improved_customer_classification_model with the required additional features, but it would never mark it as complete. Here's the query I used to create the model: CREATE OR REPLACE MODEL `ecommerce.improved_customer_classification_model` OPTIONS ( model_type='logistic_reg', labels = ['will_buy_on_return_visit'] ) AS #standardSQL SELECT * EXCEPT(fullVisitorId) FROM # features (SELECT fullVisitorId, IFNULL(totals.bounces, 0) AS bounces, IFNULL(totals.timeOnSite, 0) AS time_on_site, IFNULL(totals.pageviews, 0) AS pageviews, trafficSource.source, trafficSource.medium, channelGrouping, # mobile or desktop device.deviceCategory, # geographic IFNULL(geoNetwork.country, "") AS country FROM `data-to-insights.ecommerce.web_analytics` WHERE totals.newVisits = 1 AND date BETWEEN '20160801' AND '20170430') # train on first 9 months JOIN (SELECT fullvisitorid, IF(COUNTIF(totals.transactions > 0 AND totals.newVisits IS NULL) > 0, 1, 0) AS will_buy_on_return_visit FROM `data-to-insights.ecommerce.web_analytics` GROUP BY fullvisitorid) USING (fullVisitorId) ; And here's how I evaluated it: SELECT roc_auc, CASE WHEN roc_auc > .9 THEN 'good' WHEN roc_auc > .8 THEN 'fair' WHEN roc_auc > .7 THEN 'decent' WHEN roc_auc > .6 THEN 'not great' ELSE 'poor' END AS model_quality FROM ML.EVALUATE(MODEL ecommerce.improved_customer_classification_model, ( #standardSQL SELECT * EXCEPT(fullVisitorId) FROM # features (SELECT fullVisitorId, IFNULL(totals.bounces, 0) AS bounces, IFNULL(totals.timeOnSite, 0) AS time_on_site, IFNULL(totals.pageviews, 0) AS pageviews, trafficSource.source, trafficSource.medium, channelGrouping, # mobile or desktop device.deviceCategory, # geographic IFNULL(geoNetwork.country, "") AS country FROM `data-to-insights.ecommerce.web_analytics` WHERE totals.newVisits = 1 AND date BETWEEN '20160801' AND '20170430') # train on first 9 months JOIN (SELECT fullvisitorid, IF(COUNTIF(totals.transactions > 0 AND totals.newVisits IS NULL) > 0, 1, 0) AS will_buy_on_return_visit FROM `data-to-insights.ecommerce.web_analytics` GROUP BY fullvisitorid) USING (fullVisitorId) ));

Adam W. · Recensione inserita circa un anno fa

Kevin C. · Recensione inserita circa un anno fa

Juan Carlos B. · Recensione inserita circa un anno fa

Manish S. · Recensione inserita circa un anno fa

Jesús Arnulfo C. · Recensione inserita circa un anno fa

Ilyas N. · Recensione inserita circa un anno fa

William B. · Recensione inserita circa un anno fa

Shannon M. · Recensione inserita circa un anno fa

Shannon M. · Recensione inserita circa un anno fa

Shannon M. · Recensione inserita circa un anno fa

Andrew B. · Recensione inserita circa un anno fa

Brenda L. · Recensione inserita circa un anno fa

Dariga S. · Recensione inserita circa un anno fa

Good exercise which is a full recap for the ML Models with BigQuery ML labs serie. You need to have good SQL knowledge and remember previous exercises.

Thierry A. · Recensione inserita circa un anno fa