version control – Andrew Fairless, Ph.D.

What I Watch: Engineering For Data

By Andrew Fairless on March 16, 2022January 20, 2022

https://youtu.be/jeMQld-6BtQ What Is Engineering For Data?Jan 5, 2022Continuous Delivery “What are the big mistakes that data scientists and big organisations often make when dealing with big data? What does engineeringContinue readingWhat I Watch: Engineering For Data

What I Read: My Love / Hate Relationship With Jupyter

By Andrew Fairless on April 12, 2021April 2, 2021

https://kaskada.com/insights/my-love-hate-relationship-with-jupyter My Love / Hate Relationship With Jupyterby Max BoydBlog | A week ago | 6 — 8 mins “As a Data Scientist, I haven’t found something that fits myContinue readingWhat I Read: My Love / Hate Relationship With Jupyter

What I Read: MLOps Changing How Machine Learning Models Developed

By Andrew Fairless on February 26, 2021February 18, 2021

https://www.kdnuggets.com/2020/12/mlops-changing-machine-learning-developed.html MLOps Is Changing How Machine Learning Models Are DevelopedBy Henrik Skogstrom, Head of Growth at Valohai “Let’s look at three ways that MLOps changes how machine learning is developed:Continue readingWhat I Read: MLOps Changing How Machine Learning Models Developed

What I Read: Comparing Data Version Control Tools – 2020

By Andrew Fairless on February 9, 2021January 12, 2021

https://dagshub.com/blog/data-version-control-tools/ Comparing Data Version Control Tools – 2020Oct 31, 2020 “Managing and creating the data sets used for these models requires lots of time and space, and can quickly becomeContinue readingWhat I Read: Comparing Data Version Control Tools – 2020

What I Read: Software Tips for Data Science

By Andrew Fairless on February 2, 2021January 8, 2021

https://medium.com/swlh/software-engineering-tips-and-best-practices-for-data-science-5d85dbcf87fd Software Engineering Tips and Best Practices for Data ScienceWith great code comes great machine learningAhmed BesbesAug 28 “However, jupyter notebooks hide some serious pitfalls that may turn your codingContinue readingWhat I Read: Software Tips for Data Science

What I Read: Running Machine Learning at Scale

By Andrew Fairless on January 7, 2021December 23, 2020

https://medium.com/@jrodthoughts/some-things-uber-learned-from-running-machine-learning-at-scale-70dccdfb944d Some Things Uber Learned from Running Machine Learning at ScaleUber machine learning runtime Michelangelo has been in operation for a few years. What has the Uber team learned?Jesus RodriguezJulContinue readingWhat I Read: Running Machine Learning at Scale

What I Read: Nitpicking ML Technical Debt

By Andrew Fairless on January 2, 2021December 22, 2020

https://matthewmcateer.me/blog/machine-learning-technical-debt/ Nitpicking Machine Learning Technical DebtRevisiting a resurging NeurIPS 2015 paper (and 25 best practices more relevant than that for 2020)May 10, 2020 “Now the Tech Debt Paper is makingContinue readingWhat I Read: Nitpicking ML Technical Debt

What I Read: Monitoring Machine Learning Models in Production

By Andrew Fairless on December 20, 2020December 23, 2020

https://christophergs.com/machine%20learning/2020/03/14/how-to-monitor-machine-learning-models/ Monitoring Machine Learning Models in ProductionA Comprehensive Guide14 March 2020 “Once you have deployed your machine learning model to production it rapidly becomes apparent that the work is notContinue readingWhat I Read: Monitoring Machine Learning Models in Production

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