Feature Engineering 日本語版 from Coursera

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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。

元データから特徴への変換

特徴量エンジニアリングは多くの場合、ML プロジェクトの構築において最も長く、困難なフェーズです。特徴量エンジニアリングのプロセスでは、元データから開始し、独自のドメイン知識を用いて機械学習アルゴリズムを機能させるための特徴を作成します。このモジュールでは、どのような特徴が優れているのか、そして優れた特徴をどのように ML モデルで表現するのかについて確認します。

特徴量エンジニアリング

このモジュールでは、機械学習と統計情報の違いを確認し、BigQuery ML と Keras の両方で特徴量エンジニアリングを実行する方法について説明します。また、高度な特徴量エンジニアリングの演習も行います。

前処理と特徴の作成

このモジュールでは、Apache Beam を補完する技術である Dataflow について詳しく説明します。Apache Beam と Dataflow 両方とも、前処理や特徴量エンジニアリングを構築して実行するのに役立ちます。

特徴クロス - TensorFlow Playground

従来の機械学習では、特徴クロスはあまり重要な役割を担っていませんでしたが、最新の機械学習メソッドでは、特徴クロスは非常に有効なツールキットの一部となっています。このモジュールでは、特徴クロスが機械の学習に非常に有益となる問題の種類を認識する方法を確認していきます。

TensorFlow Transform の概要

TensorFlow Transform（tf.Transform）は、TensorFlow でデータを前処理するためのライブラリです。tf.Transform は、次のような全走査データを必要とする前処理に便利です。平均値と標準偏差による入力値の正規化、値に対するすべての入力サンプルの確認による語彙の整数値化、観測されたデータの分布に基づく入力のバケット化などです。このモジュールでは、tf.Transform のユースケースを確認します。

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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。

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

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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

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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。

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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

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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。

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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

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Career center

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

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 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

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.

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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.

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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.

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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.

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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

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.

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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

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.

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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.

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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

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.

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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.

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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

Feature Engineering 日本語版

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