I would like to share what I have found to be a very effective personal Jupyter workflow for data science development. DALL-E “An Effective Personal Jupyter Data Science Workflow” Jupyter (nee IPython) workbooks are JSON documents that allow a data scientist to mix: code, markdown, results, images, and graphs. They […]
I say: if you are a data scientist or working on an analytics project, worry over columns not rows. In analytics “rows” are instances, and “columns” are possible measurements. For example: each click on a website might generate a row recording the visit, and this row would be populated with […]
I (John Mount) am recommending a book that I just started reading. The publisher Manning recently reached out to me and asked if I would accept a free copy of Effective Data Science Infrastructure by Ville Tuulos in exchange for considering helping to promote it. No obligation to promote it, […]
I just got back from a workshop meeting called Digital Transformation of Decision Analysis. This was a workshop organized by Eyas Raddad, David Matheson, and John-Mark Agosta. It was sponsored by The Society of Decision Professionals and Microsoft. Microsoft generously hosted at their new Experience Center at the Microsoft Silicon […]
I have up what I think is a really neat tutorial on how to plot multiple curves on a graph in Python, using seaborn and data_algebra. It is great way to show some data shaping theory convenience functions we have developed. Please check it out.
I’ve now shared the code for my “Variable Utility is not Intrinsic” article here: https://github.com/WinVector/Examples/tree/main/Variable_Utility_is_not_Intrinsic. And I have also ported the entire article to Python. It is actually kind of neat to be able to compare the two and see how close doing data science in R and in Python […]
Let’s please stop saying somebody isn’t a data scientist if they haven’t memorized the innards of one obscure machine learning algorithm, or blow the right smoke during an interoo (“Kangaroo interview”, thanks Jim Ruppert for this term!). Let us, instead, think of the data scientist as the bus driver. It […]
I am sharing a new free video where I work through a great common argument that bounds expected excess generalization error as a ratio of model complexity (in rows) over training set size (again in rows), independent of problem dimension. (link) For more of my notes on support vector machines […]
I have a new short video lecture to share: “Classification as Censored Regression.”
I recently shared a bit of the history of The Science of Data Analysis. I thought I would follow that up with a quick chalk talk titled “What is Statistics?” (link)