Do I receive an accredited certificate upon completing "段階的な特徴エンジニアリング：MLデータ準備"?

Yes, upon successfully completing "段階的な特徴エンジニアリング：MLデータ準備" on Lucebra, you will receive an accredited international certificate of completion that you can add to your LinkedIn profile and resume.

Can I access this course on mobile and tablet devices?

Yes, this course is fully optimized and accessible on all iOS, Android, tablet, and desktop devices 24/7.

Are multi-language subtitles and captions available?

Yes, all video lectures feature AI-powered subtitles and transcripts in 33 languages.

Is there a deadline or time limit to complete the course?

No, you receive lifetime self-paced access to all video lectures and downloadable resources.

Are there hands-on projects and practical assignments included?

Yes, "段階的な特徴エンジニアリング：MLデータ準備" includes real-world projects, downloadable files, and practical exercises.

How long do I have access to the course materials?

Once enrolled, you receive lifetime unlimited access to all video lectures, downloadable resources, and future course updates at no extra charge.

Can I ask questions to the instructor if I get stuck?

Absolutely. You can post your questions directly in the course Q&A discussion board, where the instructor and fellow learners provide timely guidance and answers.

Is there a refund policy if the course does not fit my needs?

Yes, Lucebra provides a 7-day refund policy, provided you have watched less than 20% of the total course content. Approved refunds are credited directly to your Lucebra Credits balance for future platform purchases.

Can I watch the course on mobile devices or tablets?

Yes, all Lucebra courses are fully responsive and optimized for seamless playback across computers, laptops, tablets, and mobile devices.

Are subtitles or closed captions available for lessons?

Yes, video lectures feature AI-translated subtitles in up to 99 languages, allowing learners worldwide to follow along seamlessly in their preferred language.

Are there any prerequisites required before starting this course?

Unless specific prior requirements are stated in the course overview, basic computer literacy and an internet connection are all you need. All topics are taught step-by-step from the ground up.

Development/Data Science/Feature Engineering

Feature Engineering Step by Step: ML Data Preparation

欠損データ、スケーリング、特徴抽出、選択、高度な技術と自動化された特徴エンジニアリング

All Levels • 22 Lectures • Full Lifetime Access

Dr. Amar Massoud

Verified Master Instructor

TRAILER

Meet your instructor: Dr. Amar Massoud

19 ms

5.0 / 5.0

Global Rating

Active Students

English (US)

99 Languages Subtitles

1h 37m

Total Content

What you will learn

モデルの精度を向上させるために特徴エンジニアリング技術を理解し適用します。

偏りを特定し軽減し、公平で倫理的な特徴選択を確保します。

FeatureToolsのようなライブラリを使用して自動化された特徴エンジニアリングを実装します。

再現性とコラボレーションのために特徴のバージョンを追跡し文書化します。

Course Content

10 sections • 22 lectures • 01:37:25 total length

Introduction