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Classify Text into Categories with the Natural Language API

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61 Reviews

28ee8939ff7b06c4d3cf2f222f18d037

Excellent lab on BigQuery and Text classification. Remember to use [] around your data base table name though.

Krishna B. · Reviewed about 6 hours ago

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Sudipta B. · Reviewed about 9 hours ago

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AMRUTAM S. · Reviewed about 9 hours ago

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Tushti N. · Reviewed about 10 hours ago

5dbd2c163664ce0a88b221d8806264c3

Robert J. · Reviewed 1 day ago

3144347d614173d99f302cf71da71d70

OK

Victor David S. · Reviewed 1 day ago

1d600e198e14626dd011e7de71ea87a1

one of the instructions had the first part of the table name as "news." instead of "news_"

Brad N. · Reviewed 1 day ago

93c8a6ad467ba66cab4dde7ec2ca5e2b

David S. · Reviewed 1 day ago

A5b9ece62136913804e5a58669f4ab42

Pretty good lab, although from the outset I would like to know the if just the classification alone would be enough to derive confidence and I would have to dig to find which dataset it classifies against.

Marc L. · Reviewed 1 day ago

B6ead82deb200fcb7ecbd24956f29466

very cool

Vagish N. · Reviewed 1 day ago

Deb2906408e7a94b02eced29a5618db4

Adrian C. · Reviewed 1 day ago

41c261d1440dbfce9ef0b2a5a73c8f57

Nicolo P. · Reviewed 1 day ago

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Ashish B. · Reviewed 1 day ago

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Aman K. · Reviewed 1 day ago

B5a794a3a24d5931683a9ab16f939c52

I had some problems with the suggested query syntax: This worked: SELECT * FROM [qwiklabs-gcp-440dfc1d083ec7c1.news_classification_dataset.article_data] This didn't: SELECT * FROM `qwiklabs-gcp-440dfc1d083ec7c1.news_classification_dataset.article_data` I believe it has something to do with the default SQL settings...

Thomas J. · Reviewed 1 day ago

9ebb45c7639f862145deae5e1561b42d

Anh L. · Reviewed 2 days ago

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Chi Ming C. · Reviewed 2 days ago

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k

Yaakov M. · Reviewed 2 days ago

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Tathagat D. · Reviewed 2 days ago

D4d2cec035ffd22e4fc62b645eafb122

good lab

Sameer M. · Reviewed 2 days ago

E7e902163f664e0463818b308c2768f6

Nice

Andrew T. · Reviewed 2 days ago

E4a502f741ce385d9ac18deda10706fa

Mauricio D. · Reviewed 2 days ago

Fae4c5a1e6743b4790bcce39f815d6f6

sure

Dennison U. · Reviewed 2 days ago

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Mikael Leth K. · Reviewed 2 days ago

63e04bd9997e46f8bb91e7dc8fdb5fc6

Hari L. · Reviewed 2 days ago