Recent articles filed under Machine Learning

How to set up CUDA and PyTorch in Ubuntu 22.04 on WSL2

Created 11/2/2022 6:24:44 PM
Filed in Machine Learning

Working with machine-learning code in Windows can be quite a hassle. Often I run into problems with my tools not working properly on Windows. Recently, I even decided to convert my laptop to Ubuntu 22.04 for the time being. Which is really nice for data sciency stuff, but not great for my Powerpoint and Excel since LibreOffice sucks big time. Needless to say, I needed another solution. Especially for my deep learning setup. In this quick post I'll show you how I configured my Ubuntu 22.04 installation on Windows 11 to run CUDA and PyTorch.

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Managing machine-learning datasets with DVC

Created 10/14/2022 9:59:21 AM
Filed in Machine Learning

DVC is a data versioning tool that is designed to make it easier to work with data for machine-learning projects. It integrates with git so that you can easily keep track of your data files and track changes to them over time. It also allows you to easily share data files between different projects and collaborators. In this post I'll show you how you can start using DVC in your ML project.

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How to debug Airflow DAGs in VSCode

Created 9/10/2022 6:02:00 PM
Filed in Machine Learning

After last week's success setting up Apache Airflow I figured it would be nice to have a development setup so I can debug my own stuff. In this post, we'll look at how you can use VSCode to setup debugging for your Airflow DAGs.

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How to deploy Airflow with Kubernetes and GIT

Created 9/8/2022 7:04:31 PM
Filed in Machine Learning

When I started working on MLOps a couple of years ago I ran into Azure Machine Learning first, because that's what the community around me was using. Turns out, it's not the only product out there. I already knew this, but I Ignored other products because we were happy with Azure ML at the time. This may sound like I'm no longer happy with Azure ML and want to move away. But that's not what this is about. I think you should always explore other technology options from time to time. That's why I'm trying out Airflow on Kubernetes.

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