Ajgaonkar Practical Automated Machine Learning Using H2O.ai.

Discover the power of automated machine learning, from experimentation through to deployment to production
1. Auflage 2022
ISBN: 978-1-80107-635-7
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 396 Seiten

No detailed description available for "Practical Automated Machine Learning Using H2O.ai.".

Autoren/Hrsg.

Ajgaonkar, Salil

Fachgebiete

• Technische Wissenschaften Technik Allgemein Technik: Allgemeines
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Table of Contents - Understanding H2O AutoML Basics
- Working with H2O Flow (H2O's Web UI)
- Understanding Data Processing
- Understanding H2O AutoML Training and Architecture
- Understanding AutoML Algorithms
- Understanding H2O AutoML Leaderboard and Other Performance Metrics
- Working with Model Explainability
- Exploring Optional Parameters for H2O AutoML
- Exploring Miscellaneous Features in H2O AutoML
- Working with Plain Old Java Objects (POJOs)
- Working with Model Object, Optimized (MOJO)
- Working with H2O AutoML and Apache Spark
- Using H2O AutoML with Other Technologies

Über Autor(innen)

Ajgaonkar Salil:
Salil Ajgaonkar is a software engineer experienced in building and scaling cloud-based microservices and productizing machine learning models. His background includes work in transaction systems, artificial intelligence, and cyber security. He is passionate about solving complex scaling problems, building machine learning pipelines, and data engineering. Salil earned his degree in IT from Xavier Institute of Engineering, Mumbai, India, in 2015 and later earned his master's degree in computer science from Trinity College Dublin, Ireland, in 2018, specializing in future networked systems. His work history includes the likes of BookMyShow, Genesys, and Vectra AI.