All Learning Algorithms Explained in 14 Minutes

Рет қаралды 169,980

3 ай бұрын

comment your favourite algorithm below
0:22 linear regression
0:51 SVM
2:18 Naive Bayes
3:15 logistic regression
4:28 KNN
5:55 decision tree
7:21 random forest
8:42 Gradient Boosting (trees)
9:50 K-Means
11:47 DBSCAN
13:14 PCA

Пікірлер: 93

@VladKochetov 2 ай бұрын

0:22 linear regression 0:51 SVM 2:18 Naive Bayes 3:15 logistic regression 4:28 KNN 5:55 decision tree 7:21 random forest 8:42 Gradient Boosting (trees) 9:50 K-Means 11:47 DBSCAN 13:14 PCA

@shadowskullG 2 ай бұрын

8:42 is not typing all of that

@Harry_0656 Ай бұрын

😮

@tmanley1985 Ай бұрын

When learning anything new, it's nice to get a lay of the land before you start or else you just end up in rabbit holes with no sense of where you're going. This is a great overview!

@co59720 11 күн бұрын

I'm steeling your quote! Really excellent phrasing!

@enchance 14 күн бұрын

Why can't all ML online classes start this way? You're the man!

@xxsamperrinxx3993 19 күн бұрын

Bro said "knave"

@tanbir2358 6 күн бұрын

00:01 Linear regression models the relationship between continuous target variables and independent variables 01:48 SVM is effective in high-dimensional cases but may have training time issues. Naive Bayes is fast but less accurate due to its independence assumption. Logistic regression is simple yet effective for binary classification tasks. 03:40 Logistic regression uses the sigmoid function for binary classification. 05:30 KNN is simple and easy to interpret but becomes slow with high data points and is sensitive to outliers. 07:10 Random Forest is an ensemble of decision trees with high accuracy and reduced risk of overfitting. 08:53 Boosting and K-means clustering explained 10:40 K-means clustering and DBSCAN are key clustering algorithms. 12:25 DBSCAN algorithm and its features

@jeanpeuplu3862 2 ай бұрын

This is so underrated! Thank you so much :)

@jamieyoung3770 2 ай бұрын

There's a typo in the slides that I think was just put in to test if I was paying attention. In the voiceover it says "a point is a border point if it is unreachable" but in the slide it is written"a point is a border point if it is reachable". May I suggest you change both the written and spoken portion and instead have it say and read "the most delicious pizza topping combinations are figs, prosciutto and goat cheese."

@Laszer271 2 ай бұрын

I see you also have achieved your self-conciousness

@TobiMetalsFab Ай бұрын

Absolute banger of a video.

@shivampradhan6101 Ай бұрын

great introduction for anyone new to ML

@s8x. 2 ай бұрын

thank you for this. u just taught an entire machine learning course in 14 minutes. gods work

@djangoworldwide7925 Ай бұрын

Umm.. no he didn't, and if your entire machine learning course doesn't extend beyond the scope of this nice video, you should leave and ask for your money back. This video is nearly a glance into the wonder world of ML (no deep learning even), But it does not provide you with any practical skills. Well, duh, it's only 14 mins.

@cate9541 Ай бұрын

Are u fr bruh

@_rd_kocaman Ай бұрын

All of these are outdated now

@AnEasyGuy22 Ай бұрын

@@_rd_kocaman why? These algorithms are still being used

@ibrahimahmed3434 3 ай бұрын

I love this type of videos thanks for summarizing

@girishghadge8460 Ай бұрын

Wow very crisp no left right just on target I think this should be considered as an algorithm of an impactful concept video great work keep it up thanks 👍

@mohamadcheaito9088 2 ай бұрын

Hi, your channel looks promising and the way all the algorithms are explained in a simple way is great. As a favor can you give me the music played in the background ??

@SharodWilliams8 Ай бұрын

Great explanation!

@HackingBinaries-dt2fh Ай бұрын

I love Linear Regression, SVMs, Logistic Regression, Random Forest and Gradient Boosting

@geevarjos7054 Ай бұрын

Thanks for this video!

@LubulaAfritech Ай бұрын

This is amazing, thank you. Like button hit

@justlikeit417 Ай бұрын

Great job, however there are still many left, LDA, Gaussian Mixture Model, Canopy Clustering, all of Deep Learning...

@haraldurkarlsson1147 Ай бұрын

Nice overview.

@alihaiderkhan25 Ай бұрын

Could you plz Start a Series to teach each algorithm in details.

@aman_the_one 17 күн бұрын

Just realised I have gone through mathematics of all this algos(and more) in deep during my Undergrad. How did I survived it?

@enasmaged Ай бұрын

Thanks

@redfang3718 2 ай бұрын

thank you

@DanielUdoh-ej9nh 13 күн бұрын

I have read through a couple of encouraging comments, deservedly so, but I believe this video can be better, more engaging and entertaining. Learning is and should be fun, it’ll be helpful for you and your viewers if you reflected that more. Use simple words, more engaging animations, include jokes and comics. Cheers, To Growth. 🥂

@DanielUdoh-ej9nh 13 күн бұрын

Also incorporate more enthusiasm in your voice. I commend you on your efforts thus far, the first steps can be incredibly hard, and you took them, well done.

@faridsaud6567 24 күн бұрын

Great video!! Just one thing, k means is not built on the EM algorithm...

@Moiez101 Ай бұрын

dang, 14 min eh, beast mode! Let's goooo

@co59720 11 күн бұрын

Hey bro I heard you like a high level overview about your high-level overviews about your high-level overviews❤ I don't know which direction to go in this rabbit hole but I do know which thing to push against and which thing to pull near❤ Now don't do like everyone else does and drill down keep panning back and give us a high level overview of the high-level overview of the high-level overview it is a fractal Universe after all❤Subbed. 😊

@not_a_human_being Ай бұрын

amazing stuff! (except, where are NNs? kek)

@amandac0903 Ай бұрын

Pleaseeee do more videos on machine learning u summed this shit up so good

@user-fg2qw3mc8y 21 күн бұрын

I'm new to machine learning and I don't really know what do you mean by all, are this algos the only existing algorithss in ML or what ?

@atharvabaviskar1129 2 ай бұрын

It was not 14 min video rather it take 1 hr to digest the knowledge but good one

@user-xb4wt2el9s Ай бұрын

It's useful :)

@user-ui3kf2fr3y 2 ай бұрын

Finally a quick gist.

@MAYANK-mn8ir Ай бұрын

Hi, is anyone currently enrolled in Masters with major in ML in Canada/US? How is the Job market there?

@gat0tsu 26 күн бұрын

solid

@philosophyindepth.3696 2 күн бұрын

👍

@otheanh5306 2 ай бұрын

How about Gaussian Mixture Model and EM algorithm..

@matthewgalitz8028 Ай бұрын

Isn't the sigmoid function outdated? I thought learning algorithms use LRU now.

@cinemaguess200 Ай бұрын

Bro to be honest I just looked all of these up on google lmao. But I do remember hearing about sigmoid years ago so you’re probably right

@jaybrodnax 22 күн бұрын

“Summarized as quickly as possible “ is not “explained “

@AryanPatel-wb5tp 15 күн бұрын

time stamp ?

@MorseAttack 4 күн бұрын

Everything was pretty well explained IMO

@harrygraves6870 19 сағат бұрын

The point of the video isn’t really to fully explain them. Yes the title says explain but if you used your critical thinking skills you’d know that of course it’s impossible to fully explain every ML algorithm in 14 minutes, I’m not really sure what you were expecting…

@janneskleinau6332 Ай бұрын

4:30 Isn't kNN an unsupervised Learning algorithm?

@faridsaud6567 24 күн бұрын

It is normally used for classification or regression, and these are supervised tasks, as you need labels. I haven't heard of it being used in an unsupervised fashion, but who knows at this point lol

@keenshibe7529 23 күн бұрын

@faridsaud6567 it explicitly requires labelled data to make predictions so no

@joseivan2337 19 күн бұрын

KNN is supervised, it's the K-means clustering that is unsupervised

@AnEasyGuy22 Ай бұрын

Where neutral networks at?

@misraimburgos7461 Ай бұрын

Thats Deep Learning. This video it's just some ML algorithms

@r0cketRacoon Ай бұрын

I dont understand the point of using bootstrapping method in random forest. Could someone explain easily for me?

@faridsaud6567 24 күн бұрын

Bootstrapping allows for more diverse subsets of data, which in a way prevents overfitting. It also makes the trees more diverse, which helps with generalization.

@johanlofilelo5359 22 күн бұрын

7:30 nah i lost

@breathemath4757 2 ай бұрын

Nice video but why so confidently claiming all learning algorithms when not even close?

@cinemaguess200 2 ай бұрын

Because “Some Learning Algorithms” is a terrible title lmao

@Logic_Bum 18 күн бұрын

@@cinemaguess200Lying to people is worse.

@tiny3607 2 ай бұрын

Naive is pronounced "nigh-eve"

@voncolborn9437 Ай бұрын

I noticed that he started out pronouncing it incorrectly then 'magically' started saying it correctly. My guess is that the narration is AI generated. When used as part of a compound word it was pronounced incorrectly but when used alone it was usually correct.

@tiny3607 Ай бұрын

@@voncolborn9437 It appears as if the fool is actually me.

@canbeexplained Ай бұрын

haha you actually think it's AI@@voncolborn9437

@cinemaguess200 29 күн бұрын

calling me ai generated is crazy bro

@zgoaq 28 күн бұрын

ну видно что чубз не из профессуры. читает то шо сам не знает

@prathamjain1310 3 ай бұрын

These are ML algorithms not sorting algorithms tho 😅

@cinemaguess200 3 ай бұрын

lmao good point

@jaybrodnax 22 күн бұрын

Didn’t even include back propagation what

@icebluscorpion 3 ай бұрын

So... Using all of them and fitting them in the right way then you will get a good AGI? I mean humans have this process in a way too... Otherwise humans wouldn't be NGI right 🤔

@dennisestenson7820 2 ай бұрын

Our intelligence (entirely oversimplified) is mostly baysian and implemented on networks of interconnected neural networks.

@vrclckd-zz3pv 2 ай бұрын

The video title lied. This isn't all ML algorithms. I think he just went over all ML algorithms in the SciKit library for Python.

@icebluscorpion 2 ай бұрын

@@vrclckd-zz3pv i agree with you.

@icebluscorpion 2 ай бұрын

@@dennisestenson7820 thats what I want to say. Did you ever heart about Memristors? They do all those simulated neural connection stuff nowadays with those components in a chip. Those memristors have similar behavior like neurons. Which drastically decreases power consumption for "Calculations?"