|
|
|
|
| LEADER |
02584nmm a2200289 u 4500 |
| 001 |
EB002012182 |
| 003 |
EBX01000000000000001175081 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
220317 ||| eng |
| 050 |
|
4 |
|a Q325.5
|
| 100 |
1 |
|
|a Manjengwa, Shingai
|e host
|
| 245 |
0 |
0 |
|a Efficient machine learning
|c Shingai Manjengwa
|
| 246 |
3 |
1 |
|a Socially sustainable machine learning
|
| 250 |
|
|
|a [First edition]
|
| 260 |
|
|
|a [Sebastopol, California]
|b O'Reilly Media, Inc.
|c 2022
|
| 300 |
|
|
|a 1 video file (3 hr., 13 min.)
|b sound, color
|
| 653 |
|
|
|a Machine learning / http://id.loc.gov/authorities/subjects/sh85079324
|
| 653 |
|
|
|a Machine learning / fast
|
| 653 |
|
|
|a Apprentissage automatique
|
| 653 |
|
|
|a Machine Learning
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b OREILLY
|a O'Reilly
|
| 490 |
0 |
|
|a Artificial intelligence superstream
|
| 856 |
4 |
0 |
|u https://learning.oreilly.com/videos/~/0636920696421/?ar
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 006.3/1
|
| 520 |
|
|
|a Sponsored by Intel Machine learning has grown significantly, and with it the footprint of ML models--which can make training, deploying, and monitoring difficult and expensive. What if you could make your ML models and systems more efficient, whether in the form of cost, compute, storage, latency, or carbon footprint? Join us for this Superstream where experts dive into techniques for using fewer resources and delivering better quality. About the AI Superstream Series: This three-part series of half-day online events is packed with insights from some of the brightest minds in AI. You'll get a deeper understanding of the latest tools and technologies that can help keep your organization competitive and learn to leverage AI to drive real business results. What you'll learn and how you can apply it Understand hardware and software resources required for deep learning Learn how to optimize ML models and workloads Discover how to build robust and scalable machine learning systems Explore AI efficiencies that combat climate change This recording of a live event is for you because... You're an ML engineer or data practitioner who wants to use more-efficient algorithms and improve ML model efficiency. You're a data team leader or CDO who wants to proactively reduce the cost and resource use of ML systems and pipelines. You're a product stakeholder who wants to learn more about how ML efficiencies align with business goals. Recommended follow-up: Read Efficient Deep Learning (early release book) Watch Data Structures, Algorithms, and Machine Learning Optimization (video)
|