Opiniones sobre Crea modelos de AA con BigQuery ML: Lab de desafío

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. · Se revisó hace 28 días

Karwoo T. · Se revisó hace 28 días

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

Johan L. · Se revisó hace 28 días

Victor A. · Se revisó hace 28 días

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Da H. · Se revisó hace 28 días

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Reyna L. · Se revisó hace 28 días

Phani Kumar P. · Se revisó hace 28 días

Anand Ravi .. · Se revisó hace 28 días

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. · Se revisó hace 28 días

Vinh P. · Se revisó hace 28 días

Marius-Dumitru B. · Se revisó hace 28 días

Monica T. · Se revisó hace 28 días

Lee A. · Se revisó hace 28 días

Lee A. · Se revisó hace 28 días

Nandeesh S M. · Se revisó hace 28 días

Nandini Gajjala .. · Se revisó hace 28 días

Devansh G. · Se revisó hace 28 días

Harshit S. · Se revisó hace 28 días

lab is wired and can not pass

Hui Z. · Se revisó hace 28 días

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. · Se revisó hace 28 días

Minkush T. · Se revisó hace 28 días

Chaitanya M. · Se revisó hace 28 días