Blog - Page 13

How to train and deploy a machine learning model on AWS Sagemaker with ZenML and BentoML

Learn how to use ZenML pipelines and BentoML to easily deploy machine learning models, be it on local or cloud environments. We will show you how to train a model using ZenML, package it with BentoML, and deploy it to a local machine or cloud provider. By the end of this post, you will have a better understanding of how to streamline the deployment of your machine learning models using ZenML and BentoML.

Safoine El khabich

Dec 14, 202211 Mins Read

ZenML

Tracking experiments in your MLOps pipelines with ZenML and Neptune

ZenML 0.23.0 comes with a brand-new experiment tracker flavor - Neptune.ai! We dive deeper in this blog post.

Hamza Tahir

Dec 5, 20225 Mins Read

ZenML

ZenML's Month of MLOps Recap

The ZenML MLOps Competition ran from October 10 to November 11, 2022, and was a wonderful expression of open-source MLOps problem-solving.

Hamza Tahir

Nov 22, 20227 Mins Read

ZenML

Transforming Vanilla PyTorch Code into Production Ready ML Pipeline - Without Selling Your Soul

Transform quickstart PyTorch code as a ZenML pipeline and add experiment tracking and secrets manager component.

Felix Altenberger

Oct 27, 202224 Mins Read

ZenML

Keep the lint out of your ML pipelines! Use Deepchecks to build and maintain better models with ZenML!

Test automation is tedious enough with traditional software engineering, but machine learning complexities can make it even less appealing. Using Deepchecks with ZenML pipelines can get you started as quickly as it takes you to read this article.

Stefan Nica

Sep 6, 202217 Mins Read

ZenML

Deploy your ML models with KServe and ZenML

How to use ZenML and KServe to deploy serverless ML models in just a few steps.

Safoine El khabich

Aug 4, 202214 Mins Read

Podcast

Podcast: ML Monitoring with Emeli Dral

This week I spoke with Emeli Dral, co-founder and CTO of Evidently, an open-source tool tackling the problem of monitoring of models and data for machine learning. We discussed the challenges around building a tool that is both straightforward to use while also customizable and powerful.

Alex Strick van Linschoten

Jul 7, 20221 Min Read

ZenML

ZenML sets up Great Expectations for continuous data validation in your ML pipelines

ZenML combines forces with Great Expectations to add data validation to the list of continuous processes automated with MLOps. Discover why data validation is an important part of MLOps and try the new integration with a hands-on tutorial.

Stefan Nica

Jul 7, 202218 Mins Read

Podcast

Podcast: Edge Computer Vision with Karthik Kannan

I spoke with Karthik Kannan, cofounder and CTO of Envision, a company that builds on top of the Google Glass and using Augmented Reality features of phones to allow visually impaired people to better sense the environment or objects around them.

Alex Strick van Linschoten

Jun 30, 20221 Min Read

ZenML

How to run production ML workflows natively on Kubernetes

Getting started with distributed ML in the cloud: How to orchestrate ML workflows natively on Amazon Elastic Kubernetes Service (EKS).

Felix Altenberger

Jun 29, 202213 Mins Read

ZenML

Serverless MLOps with Vertex AI

How ZenML lets you have the best of both worlds, serverless managed infrastructure without the vendor lock in.

Alexej Penner

Jun 27, 202211 Mins Read

Podcast

Podcast: Humans in the Loop with Iva Gumnishka

This week I spoke with Iva Gumnishka, the founder of Humans in the Loop. They are an organization that provides data annotation and collection services. Their teams are primarily made up of those who have been affected by conflict and now are asylum seekers or refugees.

Alex Strick van Linschoten

Jun 23, 20221 Min Read

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