| Description |
1 online resource (408 pages) |
| Language |
In Japanese. |
| Summary |
"Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, co-founder of Claypot AI, considers each design decision--such as how to process and create training data, which features to use, how often to retrain models, and what to monitor--in the context of how it can help your system as a whole achieve its objectives. The iterative framework in this book uses actual case studies backed by ample references". |
| Subject |
Machine learning.
|
|
Artificial intelligence -- Industrial applications.
|
|
System design.
|
|
Artificial intelligence -- Design.
|
|
Computational learning theory.
|
|
Engineering -- Data processing.
|
|
Apprentissage automatique. |
|
Intelligence artificielle -- Applications industrielles. |
|
Conception de systèmes. |
|
Théorie de l'apprentissage informatique. |
|
Ingénierie -- Informatique. |
| Added Author |
Egawa, Takashi, translator.
|
|
江川崇, translator.
|
|
Hirayama, Jun'ichi, translator.
|
|
平山順一, translator.
|
| Added Title |
Designing machine learning systems : an iterative process for production-ready applications |
| Translation Of: |
Translation of: Huyen, Chip. Designing machine learning systems. First edition. Sebastopol, CA : O'Reilly Media, Inc., 2022 1098107969 (DLC) 2023275143 (OCoLC)1286145997 |
| ISBN |
9784814400409 (electronic bk.) |
|
4814400403 (electronic bk.) |
|
More Resources