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Feature Engineering 日本語版

Google Cloud Training

Google Cloud Training

Vertex AI Feature Store について学びたいとお考えですか? ML モデルの精度を向上させる方法や、最も有効な特徴を抽出するためのデータ列の見極め方を知りたいとお考えですか？このコースでは、良い特徴と悪い特徴について説明し、それらをモデルで最大限に活用できるように前処理して変換する方法を解説します。また、BigQuery ML、Keras、TensorFlow を使用した特徴量エンジニアリングに関するコンテンツとラボも含まれています。

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What's inside

Syllabus

はじめに

このモジュールでは、コースの概要とその目標を説明します。

Vertex AI Feature Store の概要

このモジュールでは、Vertex AI Feature Store を紹介します。

Read more

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Cloud AI の実践に役立つ Vertex AI Feature Store の概要を提供します。

機械学習モデルの改善に役立つ、データ列から重要な特徴を抽出する方法を学びます。

機械学習アルゴリズムに不可欠な、優良な特徴の識別と活用に役立ちます。

BigQuery ML と Keras を使用する実践的な特徴量エンジニアリング演習が含まれます。

TensorFlow と Apache Beam を活用した、高度な前処理と特徴エンジニアリングの構築を学びます。

TensorFlow Playground を通して、特徴クロスが機械学習を向上させる仕組みを理解します。

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Reviews summary

Gcp活用特徴量エンジニアリング実践解説

受講者によると、このコースはGoogle Cloudを活用した特徴量エンジニアリングを体系的に学習できる非常に有益な内容です。特に、日本語の情報が少ないVertex AI Feature Storeについて、概念から活用方法、具体的な実装まで網羅的に学べた点を高く評価する声が多く聞かれました。また、BigQuery MLやtf.Transformのような難解な概念も図解などを交えて分かりやすく解説されており、実践的な活用方法を習得できると好評です。一部の受講者からは、演習環境の構築手順がやや煩雑な点や、理論に比べて演習が少なめでデータ量が少ない点が改善点として挙げられています。全体としては、特徴量エンジニアリングの基礎知識がある人向けの実践的なコースとして推奨されています。

コースUIが最新版でない可能性あり。

"強いて言えば、コース中で利用されているUIや機能（Vertex AIなど）が、最新のものではない可能性があり...ただ、その場合でも機能の考え方や活用方法を理解できていれば、代替手段は容易に発見できますし、そこまで大きな問題ではないと思っています。"

特徴量エンジニアリングの基本知識を前提とする。

"特徴量エンジニアリングの概念自体は、ある程度理解している前提のコースだと感じました。その上で、Google Cloudのプロダクトを利用して、どのように実装していくのかを知りたい人におすすめです。"

"特徴量エンジニアリングの概念自体は、ある程度理解している人が対象だと感じました。初心者には少し難しいかもしれません。"

"データサイエンティストの方向けのコースですが、私は...Feature Engineeringの知識はほぼゼロでした。...初心者でも非常に分かりやすいコースとなっていました。"

難解な概念や活用方法が分かりやすい。

"BigQuery MLについては、クエリのみでMLモデルを作成・予測できる非常に便利な機能で、これを知れただけでも満足です。"

"tf.Transformなどの概念についても、図解などを交えながら分かりやすく解説されており、とっつきやすかったです。"

"tf.Transformのような複雑な概念についても、図解などを交えて分かりやすく解説されています。"

"特にtf.Transformは概念が難解で、公式ドキュメントだけでは理解が難しかったのですが、本コースの説明は非常に分かりやすく、実際のコードを通して理解を深めることができました。"

日本語情報が少ないテーマを体系的に解説。

"特にFeature Storeについては日本語での情報が少なく、体系的に学べる資料として大変価値があります。"

"Vertex AI Feature Storeは、日本語のドキュメントも少なく、情報が体系化されていませんでした。本コースを通して、Vertex AI Feature Storeの全体像から各コンポーネントの詳細、ユースケースまでを網羅的に学習でき..."

"特にVertex AI Feature Storeについて、その機能や活用事例、ベストプラクティスについて、体系的に学ぶことができ、理解が深まりました。"

"Vertex AI Feature Store のコンセプトや活用方法、具体的な実装について深く理解することができました。"

環境構築の手間や演習量・データサイズに課題。

"一つだけ改善点を挙げるとすれば、演習環境の構築手順が少し煩雑に感じました。"

"全体的に概念の説明が多めで、実際に手を動かす演習が少なめだと感じました。"

"演習で使用するデータの量が少なく、より実践的な規模のデータでの演習があると、より理解が深まると思います。"

"演習環境の構築手順がやや分かりにくく、環境構築でつまずく可能性があります。"

"理論の説明に偏っており、より実践的な内容の演習が欲しい。"

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Feature Engineering 日本語版 with these activities:

TensorFlow Transform のチュートリアルを完了する

Show steps

このチュートリアルでは、TensorFlow Transform を使用した前処理と特徴量エンジニアリングのスキルが向上します。

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チュートリアル環境をセットアップする
データの前処理と特徴量の作成を行う
結果を評価し、必要に応じて繰り返す

BigQuery ML で特徴量エンジニアリングの実践

Show steps

この演習では、BigQuery ML を使用して特徴量を作成し、機械学習モデルを向上させる実践的な経験が得られます。

Browse courses on BigQuery ML

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演習のセットアップとデータロード
BigQuery ML を使用して特徴量を作成する
モデルを構築し、特徴量の重要性を評価する

特徴量ストアの構築と適用

Show steps

このプロジェクトでは、Vertex AI Feature Store を使用して特徴量を管理し、モデルの精度を向上させることができます。

Browse courses on Vertex AI Feature Store

Show steps

プロジェクトのセットアップとデータ準備
特徴量ストアの作成と特徴量のインポート
モデルを構築し、特徴量の重要性を評価する

Show all three activities

Career center

Learners who complete Feature Engineering 日本語版 will develop knowledge and skills that may be useful to these careers:

Data Engineer

Data Engineers design, develop, and maintain data pipelines. They may also work on the deployment and monitoring of these pipelines. This course may be useful for aspiring Data Engineers, as it provides a foundation in feature engineering, which is used to prepare data for analysis.

See salaries and explore the career path for Data Engineer

Machine Learning Engineer

Machine Learning Engineers design, develop, and maintain machine learning systems. They may also work on the deployment and monitoring of these systems. This course may be useful for aspiring Machine Learning Engineers, as it provides a foundation in feature engineering, which is an important part of the machine learning process.

See salaries and explore the career path for Machine Learning Engineer

Data Analyst

Data Analysts collect, clean, and analyze data to help businesses make informed decisions. They may also develop visualizations and dashboards to communicate their findings. This course may be useful for aspiring Data Analysts, as it provides a foundation in feature engineering, which is essential for cleaning and preparing data for analysis.

See salaries and explore the career path for Data Analyst

Operations Research Analyst

Operations Research Analysts use their knowledge of mathematics, statistics, and computer science to solve business problems. They may also develop models to simulate and optimize business processes. This course may be useful for aspiring Operations Research Analysts, as it provides a foundation in feature engineering, which is used to prepare data for analysis.

See salaries and explore the career path for Operations Research Analyst

Quantitative Analyst

A Quantitative Analyst uses their knowledge of mathematics, statistics, and computer science to analyze financial data and make investment decisions. This course may be useful for aspiring Quantitative Analysts, as it provides a foundation in feature engineering, which is used to prepare data for analysis.

See salaries and explore the career path for Quantitative Analyst

Data Scientist

A Data Scientist uses their knowledge of statistics, data analysis, and computer science to collect, analyze, and interpret large amounts of data. They may also build models to predict future trends and outcomes. This course may be useful for aspiring Data Scientists, as it provides a foundation in feature engineering, which is essential for building accurate models.

See salaries and explore the career path for Data Scientist

Risk Analyst

Risk Analysts use their knowledge of statistics and computer science to assess and manage risk. They may also develop models to predict and mitigate risks. This course may be useful for aspiring Risk Analysts, as it provides a foundation in feature engineering, which is used to prepare data for analysis.

See salaries and explore the career path for Risk Analyst

Data Architect

Data Architects design and manage data systems. They may also work on the development and implementation of data policies and procedures. This course may be useful for aspiring Data Architects, as it provides a foundation in feature engineering, which is used to prepare data for analysis.

See salaries and explore the career path for Data Architect

Insurance Analyst

Insurance Analysts use their knowledge of insurance and finance to analyze and interpret insurance data. They may also develop recommendations for underwriting and pricing decisions. This course may be useful for aspiring Insurance Analysts, as it provides a foundation in feature engineering, which is used to prepare data for analysis.

See salaries and explore the career path for Insurance Analyst

Financial Analyst

Financial Analysts use their knowledge of finance and accounting to analyze and interpret financial data. They may also develop recommendations for investment decisions. This course may be useful for aspiring Financial Analysts, as it provides a foundation in feature engineering, which is used to prepare data for analysis.

See salaries and explore the career path for Financial Analyst

Database Administrator

Database Administrators design, implement, and maintain database systems. They may also work on the performance tuning and security of these systems. This course may be useful for aspiring Database Administrators, as it provides a foundation in feature engineering, which is used to prepare data for analysis.

See salaries and explore the career path for Database Administrator

Software Engineer

Software Engineers design, develop, and maintain software systems. They may also work on the deployment and monitoring of these systems. This course may be useful for aspiring Software Engineers, as it provides a foundation in feature engineering, which is an important part of the software development process.

See salaries and explore the career path for Software Engineer

Business Analyst

Business Analysts use their knowledge of business and technology to analyze and improve business processes. They may also develop recommendations for new products or services. This course may be useful for aspiring Business Analysts, as it provides a foundation in feature engineering, which is used to prepare data for analysis.

See salaries and explore the career path for Business Analyst

Product Manager

Product Managers are responsible for the development and launch of new products and services. They may also work on the marketing and sales of these products and services. This course may be useful for aspiring Product Managers, as it provides a foundation in feature engineering, which is used to prepare data for analysis.

See salaries and explore the career path for Product Manager

Market Researcher

Market Researchers use their knowledge of research methods and statistics to collect and analyze data about markets and consumers. They may also develop recommendations for marketing campaigns and product development. This course may be useful for aspiring Market Researchers, as it provides a foundation in feature engineering, which is used to prepare data for analysis.

See salaries and explore the career path for Market Researcher

Reading list

We've selected seven books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Feature Engineering 日本語版.

Cover image

Cover image

Hands-On Machine Learning with Scikit-Learn, Keras,...

Save

この本は、Pythonを使用した機械学習の包括的な入門書です。特徴量エンジニアリングに関する章があり、機械学習モデルの精度を向上させるために役立ちます。

(English) Hands-On Machine Learning with Scikit-Learn, Keras,...

(English) Hands-On Machine Learning with Scikit-Learn, Keras,...

(English) Hands-On Machine Learning with Scikit-Learn, Keras,...

Cover image

Cover image

Save

この本は、データマイニングと機械学習の基礎を網羅しています。特徴量エンジニアリングに関する章があり、機械学習モデルの精度を向上させるために役立ちます。

(English) Data Mining: Practical Machine Learning Tools and...

DATA MINING, 4TH EDITION

(English) Data Mining: Practical Machine Learning Tools and...

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Machine Learning in Action

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この本は、機械学習の包括的なガイドです。特徴量エンジニアリングに関する章があり、機械学習モデルの精度を向上させるために役立ちます。

(English) Machine Learning in Action

(中文) 机器学习实战 (图灵程序设计丛书 72) (Chinese Edition)

Machine Learning Design Patterns

Save

この本は、機械学習プロジェクトの設計と実装のベストプラクティスを提供します。特徴量エンジニアリングに関する章があり、機械学習モデルの精度を向上させるために役立ちます。

Machine Learning Design Patterns

Machine Learning Design Patterns

Cover image

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Machine Learning Engineering

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この本は、機械学習モデルの開発、デプロイ、監視のプロセスを網羅しています。特徴量エンジニアリングに関する章があり、機械学習モデルの精度を向上させるために役立ちます。

(English) Machine Learning Engineering

(English) Machine Learning Engineering

Machine Learning Con Pytorch Y Scikit Lean

Save

この本は、Pythonを使用した機械学習の包括的な入門書です。特徴量エンジニアリングに関する章があり、機械学習モデルの精度を向上させるために役立ちます。

(Español) Machine Learning con PyTorch y Scikit-Learn:...

Cover image

Cover image

Machine Learning with R

Save

この本は、Rを使用した機械学習の包括的な入門書です。特徴量エンジニアリングに関する章があり、機械学習モデルの精度を向上させるために役立ちます。

(English) Machine Learning with R - Fourth Edition: Learn...

(English) Machine Learning with R - Second Edition: Expert...

(English) Machine Learning with R - Third Edition: Expert...

(Italiano) Machine Learning con R: Conoscere le tecniche per...

(English) R: Unleash Machine Learning Techniques

(English) Machine Learning with R: Learn How to Use R to...

(中文) Machine learning and R language (3rd edition of the...

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Effort

受講期間: 2 週間（5～7 時間/週）

Level

Intermediate

Via

Coursera

Institution

Google Cloud

Instructor

Google Cloud Training

Language

日本語

Transcript

English

This course belongs to a collection called Machine Learning with TensorFlow Google Cloud 日本語版. It's comprised of five courses:

Launching into Machine Learning 日本語版
Art and Science of Machine Learning 日本語版
Feature Engineering 日本語版 (viewing)
How Google does Machine Learning 日本語版
Intro to TensorFlow 日本語版

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Cloud AI の実践に役立つ Vertex AI Feature Store の概要を提供します。

機械学習モデルの改善に役立つ、データ列から重要な特徴を抽出する方法を学びます。

機械学習アルゴリズムに不可欠な、優良な特徴の識別と活用に役立ちます。

BigQuery ML と Keras を使用する実践的な特徴量エンジニアリング演習が含まれます。

TensorFlow と Apache Beam を活用した、高度な前処理と特徴エンジニアリングの構築を学びます。

TensorFlow Playground を通して、特徴クロスが機械学習を向上させる仕組みを理解します。

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