The Model’s the thing

Chris Anderson proclaims: Theory is dead, long live data! Away with every theory “of human behavior, from linguistics to sociology. Forget taxonomy, ontology, and psychology.” … we don’t need to fit data into theory in order to create opportunities for more … Mehr… →

Bowker

»First we take Manhattan, then we take Berlin.« Leonard Cohen »First we take Chris Anderson, then we take Latour.« Geoffrey C. Bowker (2014)

detection

For instance, OpenFace uses dlib for face detection which was trained on Labeled Faces in the Wild images which in turn used the Viola-Jones face detection that relies on Haar cascade classifier (no longer state-of-the-art) and these images were scraped from internet almost 10 years ago. … Mehr… →

Deep Saturation

Vectorization, the deep saturation of the table by algebra, constitutes all relations as movements of transformation, diagonalization, inversion or rotation. Mackenzie 2017:76

Traversing Date

Drawing lines or flat surfaces at various angles and directions is perhaps the main way in which the volume of data is traversed, and a relation between input and output, between predictors and prediction, consolidated as a loci or data … Mehr… →

Table

The table or the row-column addressable grid is common to all of [machine learning] datasets. And yet, as we are about to see, machine learning in many ways deals with the collapse or liquidation of tabular datasets. Mackenzie 2017:57 #table … Mehr… →

Vectoral Space

The operational power of machine learning locates data practice in an expanding epistemic space. The space derives, I will suggest, from a specific operational diagram that maps data into a vector space. Mackenzie 2017:52

Statistical algorithmic diagrams

In #machinelearning, coding changes from what we might call symbolic logical diagrams to statistical algorithmic diagrams. Mckenzie 2017:46

Coding cultures

…the use [of] programming languages such as Python and R more than specialized commercial statistical and data software packages such as Matlab, SAS or SPSS  is perhaps symptomatic of shifts in computational culture. Coding cultures are crucial to the recent … Mehr… →

Relations

Materially, code is only one element in the diagram of machine learning. It displays, with greater or lesser degrees of visibility relations between a variety of forces (infrastructures, scientific knowledges, mathematical formalisations, etc.). McKenzie 2017:45 #AI #ML