Skip to main content

1.1 Memorization, Learning and Classification

Memorization, Learning and Classification

https://rumble.com/vbp5su-memorization-learning-and-classification.html

Memorization - Store the contents of a set of observations

Learning - When a constraint is imposed with a requirement to communicate outside the system, then learning occurs, a new representation of the observations is necessary, more efficient, abstractions occur.

Classification - A judgment statement, good/bad, a category is labeled with a quality

While learning provides a better quantity, more efficient representation, classification provides a quality.


Notes:

1. Short term memory is constrained and communicated to long term memory typically at night, most learning occurs at night

2. Maimonidies in the Guide opens with the distinction between truth-falsity vs. good-bad

3. Prof. K. Smith, Human and non-human communication


Comments

Popular posts from this blog

III) Metrics

III) Metrics One of these things is not like the other -- but two of these things are distant from a third. I grew up with Brisk Torah, more specifically my father was a Talmid of Rabbi Joseph Soloveichik and dialectic thinking was part and parcel of our discussions.  Two things, two dinim, the rhythm in the flow between two things.  Dialectics not dichotomies.  The idea espoused by the Rambam in his description of Love and Awe, mutually exclusive, we travel between them. Why create duality?  Dialectics or dichotomies provide a powerful tool, but what is it that tool? What is the challenge? I think the Rabbinic language might be נתת דברך לשיעורים, 'your words are given to degrees', the idea being that without clear definitions we are left with vague language, something is more than something else, ok, but how much more? This I think is the reasoning for the first of the twenty one questions I was taught by my father's mother, 'is it bigger than a breadbox?',...

1.65 Phase transitions, a measure of learning

Phase transitions, a measure of learning https://rumble.com/vcj8fk-1.65-phase-transitions-a-measure-of-learning.html Lets compare KMeans to faddc KMeans faddc That was quite dramatic, how did we get there: KMeans faddc Neat right, KMeans spreads its representations equally across the entire dataset, minimising the global loss of information The thing to notice with faddc is that the representation is very stable up to a point, at a certain point there is a dramatic shift in the representation.   Here I graph the derivative energy, the change, the difference between the distortion given each 'k'....

Too Much Data -- summary post

Here is a set of summary links: I) We live in the Information Age https://data-information-meaning.blogspot.com/2019/03/we-live-in-information-age.html II) Too much data https://data-information-meaning.blogspot.com/2019/03/too-much-data.html III) Metrics https://data-information-meaning.blogspot.com/2019/03/metrics.html IV) Abstractions and judgements https://data-information-meaning.blogspot.com/2019/03/abstractions-and-judgements.html V) How do we know we made a reasonable judgement? https://data-information-meaning.blogspot.com/2019/04/how-do-we-know-we-made-reasonable.html ---- https://data-information-meaning.blogspot.com/2019/04/scale-hierarchy-and-distance-metrics.html