Machine Learning Systems
Designs that scale
$144.30
- Paperback
275 pages
- Release Date
25 September 2018
Summary
Machine learning applications autonomously reason about data at massive scale. It’s important that they remain responsive in the face of failure and changes in load. But machine learning systems are different than other applications when it comes to testing, building, deploying, and monitoring.
Reactive Machine Learning Systems teaches readers how to implement reactive design solutions in their machine learning systems to make them as reliable as a well-built web app…
Book Details
| ISBN-13: | 9781617293337 |
|---|---|
| ISBN-10: | 1617293334 |
| Author: | Jeff Smith |
| Publisher: | Manning Publications |
| Imprint: | Manning Publications |
| Format: | Paperback |
| Number of Pages: | 275 |
| Release Date: | 25 September 2018 |
| Weight: | 420g |
| Dimensions: | 14mm x 185mm x 235mm |
Jeff Smith
Jeff Smith builds large-scale machine learning systems using Scala and Spark. For the past decade, he has been working on data science applications at various startups in New York, San Francisco, and Hong Kong. He blogs and speaks about various aspects of building real world machine learning systems.
Returns
This item is eligible for free returns within 30 days of delivery. See our returns policy for further details.