Comments
SaifKhayoon OP t1_j6dfnuz wrote
The title is a bit inaccurate beside simplifying the whole of the field to just "statistics" I grouped in AI with Machine learning, when AI is actually a humongous field encompassing things from video game enemies to roombas, machine learning learning is a field within AI and deep learning which is the most impressive is a subfield of that
ZennyRL t1_j6eehw2 wrote
Certainly sounded easier than it is, most of these terms even in the first chapter go way over my head
knockonformica t1_j6ejgn0 wrote
This is absolutely incredible! It's a great visualization for statistics and probability. I'm always reading academic medical studies & having a stats refresher like this is so helpful. I know a bunch of colleagues would benefit from seeing the concepts portrayed visually.
I am going to share this with any students I have. Thanks again!!
canttouchmypingas t1_j6ey1q8 wrote
Thanks for the follow up comment I was about to rage about the statistics thing
reddituseronebillion t1_j6f5q7l wrote
It's really just linear algebra and calculus in disguise.
TheDailyBean t1_j6f67u8 wrote
Ha. This guy knows.
SteelerSuperFan t1_j6fg6mj wrote
Book marked for later
SpinCharm t1_j6fnxwn wrote
Interesting but doesn’t really start to draw a line between machine learning and AI. It lays a foundation of understanding of statistics, but stops before it relates them to the broader concepts of machine learning, ie How are these statistical forms used within machine learning?
pixeladrift t1_j6foxrz wrote
It’s really just artificial intelligence in abbreviation.
Leonos t1_j6fs79e wrote
>> You may wish to use the visualization to verify some of the following set identities.
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Yourbubblestink t1_j6fyta7 wrote
The sad news kids. Chat GPT can already do all this shit faster than you.
dutch665 t1_j6g17yi wrote
This is where I started
rbcornhole t1_j6g2m2p wrote
Don't feel bad, the title is wildly over simplifying it.
SaifKhayoon OP t1_j6g4dg3 wrote
Here's a list of example sets to try:
>A ∪ B
A union B combines both circles
>A' = {1, 2, 3} complement
Demonstrates complement of a set (A' = {all elements not in A})
>(A ∪ B)' = complement of union of A and B
De Morgan's law for complement of union and intersection
>A ∩ B = ∅
Demonstrates disjoint sets (sets with no common elements)
>A ∪ B = U
Together make up the universal set
tyen0 t1_j6g4pj7 wrote
same.... maybe some day. ;)
wysiwywg t1_j6g69m4 wrote
NoYou786 t1_j6hq4kt wrote
OooOoooO
leaflavaplanetmoss t1_j6hw5mf wrote
This has been around for a couple of years, it's not meant to be a primer for AI/ML; it's a visual introduction to statistics and probability. OP just couched it in terms of AI/ML because statistics and probability form the basis of many AI/ML models, like classification (which is really just logistic regression), so understanding statistics is an important foundation for AI/ML study.
ThatCook2 t1_j6miwhi wrote
This is well made!
cdgleber t1_j6deucn wrote
Holy wow this is good