ML-Modelle mit BigQuery ML erstellen: Challenge-Lab Rezensionen

44325 Rezensionen

The instructions in step 3 are ambiguous. There's no way to know whether the model was created according to the instructions, or whether the evaluation step doesn't pass the checker. Even after 7 separate attempts to run step 3, I can't pass the checker. ## Task 3. Improve model performance with Feature Engineering and Evaluate the model to see if there is better predictive power """ In this task, use dataset features that may help the customer_classification_model model better understand the relationship between a visitor's first session and the likelihood that they purchase on a subsequent visit. Now add some new features and create a second machine learning model called improved_customer_classification_model. How far the visitor got in the checkout process on their first visit Where the visitor came from(traffic source: organic search, referring site, etc..) Device category(mobile, tablet, desktop) Geographic information(country) Now, evaluate the newly created model improved_customer_classification_model to see if there is better predictive power than customer_classification_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, MAX(CAST(h.eCommerceAction.action_type AS INT64)) AS latest_ecommerce_progress, IFNULL(geoNetwork.country, "") AS country, trafficSource.source as traffic_source, device.deviceCategory as device_category, IFNULL(geoNetwork.country, "") AS the_country FROM `data-to-insights.ecommerce.web_analytics`, UNNEST(hits) as h WHERE totals.newVisits = 1 AND date BETWEEN '20160801' AND '20170430' # train on first 9 months GROUP BY fullVisitorId, bounces, time_on_site, the_country, traffic_source, device_category) 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); # 3.5 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, ( SELECT * EXCEPT(fullVisitorId) FROM # features (SELECT fullVisitorId, IFNULL(totals.bounces, 0) AS bounces, IFNULL(totals.timeOnSite, 0) AS time_on_site, MAX(CAST(h.eCommerceAction.action_type AS INT64)) AS latest_ecommerce_progress, IFNULL(geoNetwork.country, "") AS country, trafficSource.source as traffic_source, device.deviceCategory as device_category, IFNULL(geoNetwork.country, "") AS the_country FROM `data-to-insights.ecommerce.web_analytics`, UNNEST(hits) as h WHERE totals.newVisits = 1 AND date BETWEEN '20160801' AND '20170430' # train on first 9 months GROUP BY fullVisitorId, bounces, time_on_site, the_country, traffic_source, device_category) 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) ));

Jennifer M. · Vor 28 Tage überprüft

Karwoo T. · Vor 28 Tage überprüft

BUG in task 2 and 3. Cant be completed in some cases

Johan L. · Vor 28 Tage überprüft

Victor A. · Vor 28 Tage überprüft

Karwoo T. · Vor 28 Tage überprüft

Da H. · Vor 28 Tage überprüft

Karwoo T. · Vor 28 Tage überprüft

Victor A. · Vor 28 Tage überprüft

Reyna L. · Vor 28 Tage überprüft

Phani Kumar P. · Vor 28 Tage überprüft

Anand Ravi .. · Vor 28 Tage überprüft

in this lab, the second test case is passing whatever we do, even after evaluating the model, it is not seen as pass. Could you pls check if there is any issue in that ?

Subhash Y. · Vor 28 Tage überprüft

Vinh P. · Vor 28 Tage überprüft

Marius-Dumitru B. · Vor 28 Tage überprüft

Monica T. · Vor 28 Tage überprüft

Lee A. · Vor 28 Tage überprüft

Lee A. · Vor 28 Tage überprüft

Nandeesh S M. · Vor 28 Tage überprüft

Nandini Gajjala .. · Vor 28 Tage überprüft

Devansh G. · Vor 28 Tage überprüft

Harshit S. · Vor 28 Tage überprüft

lab is wired and can not pass

Hui Z. · Vor 28 Tage überprüft

very bad, i dont know why i cannot pass task 2 and 3, while i have done dozens of methods to evaluate the models, if i'm really doing something incorect, the lab checks should tell me something useful , rather than keeping giving vague msg for learner to guess, it's a waste of time..

WEI TAO VICTOR Y. · Vor 28 Tage überprüft

Minkush T. · Vor 28 Tage überprüft

Chaitanya M. · Vor 28 Tage überprüft

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