PinnedInTDS ArchivebyPatrick Brus·Feb 24, 2024How to Write Clean Code in PythonTop takeaways from the book Clean CodeA response icon15A response icon15
PinnedInTDS ArchivebyPatrick Brus·Sep 19, 2022MLOps: Bring your Models into Production using the CloudContinuous Deployment Pipeline of your Deep Learning Model to the Cloud using AWS, S3 and CloudFormationA response icon1A response icon1
PinnedInTDS ArchivebyPatrick Brus·Dec 16, 2021Continuous Deployment Pipeline using Github Actions, Docker and AWSAutomatically Deploying a Flask ML Application to AWS Elastic BeanstalkA response icon2A response icon2
PinnedInTDS ArchivebyPatrick Brus·Sep 28, 2022Why You Should Learn Machine Learning Engineering and Not Data ScienceAnd how you can startA response icon12A response icon12
InData Science CollectivebyPatrick Brus·Jan 7DataOps vs. MLOps: Why modern AI projects can’t succeed without bothModern AI doesn’t fail because of weak models. It fails due to the absence of DataOps and MLOps.A response icon2A response icon2
InData Science CollectivebyPatrick Brus·May 26, 2025Why your machine learning models never reach production — and how to fix thatA practical look at why machine learning projects never make it to production — and how MLOps practices can help
InLevel Up CodingbyPatrick Brus·Feb 4, 2024AWS Data Engineering Nanodegree: Expectation vs. RealityLearnings and Insights
InLevel Up CodingbyPatrick Brus·Aug 16, 2023The Future of Data Science: How ChatGPT’s Code Interpreter is Reshaping the FieldOpenAI just released their new feature, called Code Interpreter, as beta to all their premium users.
InTDS ArchivebyPatrick Brus·Apr 25, 2023Democratizing Machine Learning with AWS SageMaker AutoMLAn Overview
InTDS ArchivebyPatrick Brus·Nov 14, 2022How to Solve Every ML Problem with Low-CodeAn Introduction to the Python Library PyCaretA response icon2A response icon2