Lynda DevOps for Data Scientists Data Science Development Practices 05 Experimenting with data features and algorithms en srt

Lynda DevOps for Data Scientists
Data Science Development Practices 05 Experimenting with data features and algorithms en srt

Name	Lynda - DevOps for Data Scientists	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	56.1 MB
Total Files	34
Hash	F07EB5BF31CA2CFFF54765FCD8BE683B372E09A8

/2.1. Data Science Development Practices/05.Experimenting with data, features, and algorithms.en.srt	2.7 KB
/2.1. Data Science Development Practices/05.Experimenting with data, features, and algorithms.mp4	4.5 MB
/2.1. Data Science Development Practices/06.Testing and validating models.en.srt	2.9 KB
/2.1. Data Science Development Practices/04.Collecting and munging data.en.srt	4.4 KB
/2.1. Data Science Development Practices/03.Data science and software engineering.en.srt	2.6 KB
/2.1. Data Science Development Practices/06.Testing and validating models.mp4	2.6 MB
/2.1. Data Science Development Practices/04.Collecting and munging data.mp4	4.1 MB
/2.1. Data Science Development Practices/03.Data science and software engineering.mp4	2.8 MB
/3.2. Data Science Models to Production/07.Version control for data science models.en.srt	4.7 KB
/3.2. Data Science Models to Production/08.Predictive Model Markup Language.en.srt	3.4 KB
/3.2. Data Science Models to Production/09.Deploying models with automation tools.en.srt	2.6 KB
/4.3. Deployment Practices/12.Securing the data science models in production.en.srt	7.7 KB
/4.3. Deployment Practices/10.Deploying to staging environment.en.srt	2.0 KB
/4.3. Deployment Practices/13.Monitoring models in production.en.srt	4.4 KB
/5.4. Data Science Models in Containers/15.Creating a Dockerfile for data science models.en.srt	4.2 KB
Showing first 15 files of 34 total files