Breaking into machine learning engineering

• Titel: Breaking into machine learning engineering
• Titelzusatz: a primer on MLE skills and interviews for beginners
• Mitwirkende: Chang, Susan Shu [MitwirkendeR]
• Institutionen: O'Reilly (Firm), [Verlag]
• Ausgabe: [First edition].
• Verlagsort: [Sebastopol, California]
• Verlag: O'Reilly Media, Inc.
• E-Jahr: 2024
• Jahr: [2024]
• Umfang: 1 online resource (1 video file (57 min.))
• Illustrationen: sound, color.
• Fussnoten: Online resource; title from title details screen (O’Reilly, viewed October 10, 2024)
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Apprentissage automatique
• Sach-SW: Intelligence artificielle
• Sach-SW: artificial intelligence
• Sach-SW: Instructional films
• Sach-SW: Nonfiction films
• Sach-SW: Internet videos
• Sach-SW: Films de formation
• Sach-SW: Films autres que de fiction
• Sach-SW: Vidéos sur Internet
• K10plus-PPN: 1907896767
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m4611075222
• Lokale URL Inst.: Zum Volltext

Abstract

Machine learning powers all the major tech companies–all major search engines, web browsers, media sites (such as Spotify and Youtube) use machine learning. One in ten enterprises use ML/AI applications such as chatbots, fraud detection, and other algorithms. As such, it is a massive industry bringing in billions of dollars of value, with high demand for talent. This course teaches learners how to get started in the ML field: what skills to learn and what MLE interviews entail. This course gives an overview of various MLE roles (including GenAI), interview components such as ML theory, programming, and behavioral interviews, and what skills job seekers need to prepare. After this course, you will walk away with a clear set of steps you can take to break into machine learning engineering.