ZenML Blog

The latest news, opinions and technical guides from ZenML.
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ZenML
6 Mins Read

Detecting Fraudulent Financial Transactions with ZenML

A winning entry - 2nd prize winner at Month of MLOps 2022 competition.
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ZenML
11 Mins Read

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.
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ZenML
24 Mins Read

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.
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ZenML
14 Mins Read

Deploy your ML models with KServe and ZenML

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

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).
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ZenML
11 Mins Read

Serverless MLOps with Vertex AI

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

How to get the most out of data annotation

I explain why data labeling and annotation should be seen as a key part of any machine learning workflow, and how you probably don't want to label data only at the beginning of your process.
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ZenML
14 Mins Read

Will they stay or will they go? Building a Customer Loyalty Predictor

We built an end-to-end production-grade pipeline using ZenML for a customer churn model that can predict whether a customer will remain engaged with the company or not.
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ZenML
12 Mins Read

All Continuous, All The Time: Pipeline Deployment Patterns with ZenML

Connecting model training pipelines to deploying models in production is seen as a difficult milestone on the way to achieving MLOps maturity for an organization. ZenML rises to the challenge and introduces a novel approach to continuous model deployment that renders a smooth transition from experimentation to production.
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