generally, Exploratory Data Analysis (EDA) is done to answer a question. as i never practised statistics, it is not that “refined” but, hopefully, has the benefit of applied understanding from an “outsider” – it took me awhile to try and prepare this for a broader audience. that said, i’m always open to make the content more understandable to the “layperson”.

here’s the link to my updated GitHub repository:

https://github.com/LinsAbadia/Python/blob/master/Analyses/EDA.ipynb

i’m loathe to admit i only learned the difference a few years ago. both are abbreviations using the first letters of a word (typically the initial letter only).

essentially, acronyms can be read/pronounced as they mostly form a word (or something similarly sounding to one). for initialisms, you say each letter and the “short-cut” need not form a recognised word.

i don’t mean to be pedantic or correct anyone – i just find it nice-to-know.

i ran into this recently. i almost forgot about this since the last time i “discussed” this was in school (either “late” primary or secondary).

it’s a cross between a question mark and an exclamation point. it’s a punctuation mark designed for an “exclamatory rhetorical question” (whatever that actually is).

out of curiosity, has anyone seen it actually used in the wild?

initially, i just planned on posting a “short” “blurb” on my blog and GitHub Python page as there seemed to me to be a “virtual triangle” among machine learning, statistics, and data visualisation. i’m still likely to make a brief GitHub “file” but upon serious reflection this post may not be a “cursory” post.

it took me awhile to come up with this post because i was partly busy with an online machine learning course, and, frankly, didn’t know what to write – and i’m finding it difficult to figure out how to do it – it didn’t help that there was a “time-consuming” upgrade of the Jupyter notebook environment that i use to store my ipynb files online.

my last experience started me thinking on how i learn- i still need to reflect more on it. i’ve done “ok” academically but i’ve discovered i can understand better if “alternatives” are provided for me to choose from. programming is, essentially, divergent: that is, sometimes there is more than a single way to arrive at an “acceptable solution”. why can’t “formal” education be that way? i know that the human brain can be easily overloaded by many things but perhaps offering a few choices might result in more students understanding. i’m realistic and pragmatic enough to understand that most teachers are overworked (at least those that care about the development of others) and that maybe there needs to be a more “active” open-source community like coding: sharing can make lighter work.

here is my initial attempt at my updated repository:

https://github.com/LinsAbadia/Python/blob/master/Machine%20Learning/Learning.ipynb

apparently, i was wrong: both think and thing are acceptable. like so many others, i had been inadvertently “influenced” by the Judas Priest lyrics.

i discovered my mistake when i “played” commonly confused words : https://www.merriam-webster.com/word-games/more-confusing

this had caused me to do a bit of digging and i stumbled upon this article: https://www.theguardian.com/media/mind-your-language/2014/nov/18/mind-your-language-another-think

if mondegreens are often misheard lyrics, what do call “misinterpreted” language from a song?

although we use the metric system in Australia, i still mainly use the English (or Imperial, pick your poison) equivalents for height and weight. maybe IMHO it makes more “sense”, maybe it’s just a force of habit (as we use a “mixed” version in the Philippines. strangely, we’ve not committed to one nor the other), or maybe some kind of combination of these.

apparently, lb is short for the Latin libra which roughly translates to “pound weight” – this etymology is also the root of the currency.

i partly recall the jingle to fully “convert” the population to metric that’s why i remember these ratios: cm = in * 2.54; lbs = kg * 2.2…

i know the Aussie expression (it is Kiwi depending on whom you ask) of: yeah, nah, yeah can differ based on context and the actual variant used – in this case it indicates ambivalence.

it’s hard to believe that it’s been nearly 12 years since i stopped work. don’t get me wrong – i was really glad to see them and i had seen some of them over the years but something was slightly different this time.

i had to reflect on it to figure out why. i don’t know if it was because my wife now worked for the same organisation, the place where we ate was just a stone’s throw away from our offices, they were “purely” social visits before, it was something else, or a combination of some of these factors. there were moments (admittedly, few and far in between) when the conversation was lightly peppered with “shop talk”.

this sounds like i’m nostalgic for work but i still recall it was a hardly a “bed of roses”. the core group is still around even after all these years (which is a testament to my former boss’ management skills). i think, to some extent, i miss the challenge – sure the team sometimes handled things differently, but our goal was, ultimately, to arrive at a singular mitigation strategy.

i guess i felt a little frustrated that stopping wasn’t really on my own terms and it wasn’t a conscious decision on my part: in short i didn’t have a choice.

i feel there were still things i could’ve “accomplished” and my contribution would’ve been much “greater”. Oh, well…