ML をデータ パイプラインに組み込むと、データから分析情報を抽出する能力を向上できます。このコースでは、Google Cloud でデータ パイプラインに ML を含める複数の方法について説明します。カスタマイズがほとんど、またはまったく必要ない場合のために、このコースでは AutoML について説明します。よりカスタマイズされた ML 機能については、Notebooks と BigQuery の機械学習（BigQuery ML）を紹介します。また、Vertex AI を使用して ML ソリューションを本番環境に導入する方法も説明します。
Smart Analytics, Machine Learning, and AI on GCP 日本語版
Smart Analytics, Machine Learning, and AI on GCP 日本語版
This course is part of multiple programs.
Instructor: Google Cloud Training
Access provided by FutureX
Gain insight into a topic and learn the fundamentals.
31 reviews
Intermediate level
Some related experience required
7 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
ML、AI、ディープラーニングの違いを理解する。
非構造化データに対する ML API の使用について考察する。
Notebooks から BigQuery コマンドを実行する。
BigQuery で SQL 構文を使って ML モデルを作成する。
Skills you'll gain
Tools you'll learn
Details to know
Shareable certificate
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Assessments
6 assignments
Taught in Japanese
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- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
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There are 8 modules in this course
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