
Lynda Deploying Scalable Machine Learning for Data Science-XQZT
Size: 355.92 MB
Genre: eLearning | Language: English
Size: 355.92 MB
Genre: eLearning | Language: English
Another exquisit release
Lynda.Deploying.Scalable.Machine.Learning.for.Data.Science-XQZT
Title: Deploying Scalable Machine Learning for Data Science
Publisher: Lynda
Size: 179M (186614477 B)
Files: 4F
Date: 08/18/2018
Course #: 711823
Type: Big Data
Published: 8/17/2018
Modified: N/A
URL: www.lynda.com/course-tutorials/Deploying-Scalable-Machine-Learning-Data-Science/711823-2.html
Author: Dan Sullivan
Duration: 1h 43m
Skill: Intermediate
Exer/Code: [X]
Installation:
Unpack that shit, run that shit
Notes:
Machine learning models often run in complex production
environments that can adapt to the ebb and flow of big data. The
tools and practices that help data scientists rapidly
cemebuildc/eme machine learning models are not sufficient to
cemedeployc/eme those models at scale. To deliver scalable
solutions, you need a whole new toolset. This course provides data
scientists and DevOps engineers with an overview of common
design patterns for scalable machine learning
architectures, as well as tools for deploying and
maintaining machine learning models in production.
Instructor Dan Sullivan reviews three technologies that enable
scalable machine learning: services that expose models through
APIs, containers for deploying models, and orchestration tools
like Kubernetes that help manage containers and clusters. Plus, get
tips for monitoring the performance of your services in
production environments.

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