Bit width defender
Was just thinking that since is becoming common practice in data science to normalize numeric data, it would be neat to have a new data type with limited integer registers but high capacity in the fractionals. Might be more bit width efficient for this use case.
Ok just offered a suggestion to the IEEE workgroup behind standard 754 for floating point arithmetic and thought would formalize with a demonstration to flesh out the details.
To offer a little background, IEEE-754 is the standard that defines in-memory representations of floating point numbers, which for an arbitrary number (e.g. 1234.56), when that…
From my family tree to yours
For further readings please check out A Table of Contents, Book Recommendations, and Music Recommendations. For more on Automunge: automunge.com
Eat your heart out Confucius
An aphorism is a condensed form of writing in which one can find the theme of a novel, the lesson of an age, or a pithy diversion.
No aphorism is complete without context, but one may feel free to bring their own.
If the universe is a vast ocean, then consciousness is the foam from waves breaking on the shore.
Manifest destiny does not exist, frontiers must be earned.
Follow those bees who reach for the farthest flower.
Just because you can’t vocalize some understanding does not mean that it can’t be conveyed.
A single tear drop holds more salt…
On Causal Inference
Ok so as a quick confession I’ve been meaning to write an essay on causal inference for quite some time now. Have read a few books (like Peters, Janzing, and Schölkop’s Elements of Causal Inference), read a few papers (like Judea Pearl’s The Seven Tools of Causal Inference), read some blog posts (like Bruno Gonçalve’s DFS blog), and heck even did a stint in an entertaining altdeep.ai workshop on related material taught by Robert Ness. I think what has held me back was a real struggle on finding a proper framing. This subject is somewhat complex, so a comprehensive overview…
If you believe the impossible, the incredible can come true.
Field of Dreams is a 1989 American sports fantasy drama film written and directed by Phil Alden Robinson, adapting W. P. Kinsella’s 1982 novel Shoeless Joe. The film stars Kevin Costner, Amy Madigan, James Earl Jones, Ray Liotta and Burt Lancaster in his final film role. It was nominated for three Academy Awards, including for Best Original Score, Best Adapted Screenplay and Best Picture. In 2017, the film was selected for preservation in the United States National Film Registry by the Library of Congress as being “culturally, historically, or aesthetically significant”. (via wikipedia, image via IMDB)
The Preprint
Abstract
Missing data is a fundamental obstacle in the practice of data science. This paper surveys a few conventions for imputation as available in the Automunge open source python library platform for tabular data preprocessing, including “ML infill” in which auto ML models are trained for target features from partitioned extracts of a training set. A series of validation experiments were performed to benchmark imputation scenarios towards downstream model performance, in which it was found for the given benchmark sets that in many cases ML infill outperformed for both numeric and categoric target features, and was otherwise at minimum within noise…
Hashtag #ICLR2021
Introduction
With the annual ICLR conference right around the corner, have decided this year to reconsider my approach for explorations. You see there has become somewhat of an explosion of papers accepted at these top tier machine learning research venues, and well finally came to the conclusion that if you don’t approach with an objective in mind an attendee is likely to get somewhat overwhelmed amongst the forest of signal and noise. So what will be my reward function for this year’s ICLR? Trying to get caught up in the specialty of reinforcement learning.
Of course I’ve had a few brush-ins…
Competition is healthy
Introduction
As the Automunge project closes in on two years of full time focus, figured it would be worth a little reflection on the surrounding competitive environment, which has gone through some considerable changes in the time since inception. Automunge was conceived as a platform for tabular data preprocessing, basically with the intent to automate most if not all of the data science workflow immediately preceding the application of machine learning.
We made an early decision to build on top of the Pandas dataframe library, which for our purposes has served quite well, however this library does have some built in…
Small update to appendix A associated with parameter consolidations in 5.94
Nicholas Teague
Writing for fun and because it helps me organize my thoughts. I also write software to prepare data for machine learning at automunge.com
