All Machine Learning algorithms intuitively explained in 17 min
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I just started my own Patreon, in case you want to support!
Patreon Link: https://www.patreon.com/c/InfiniteCodes
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In this video I will go through all machine learning algorithms in less than 17 minutes to get you an intuitive understanding of how they work and how they relate to each other as well as help you decide how to pick the right one for your problem. Going all the way from Linear Regression to Neural Networks / Deep Learning and Unsupervised Learning.
Also Watch:
How to Learn Machine Learning in 2024 (7 step roadmap) https://youtu.be/jwTaBztqTZ0
The Math Skills that make Machine Learning easy (and how you can learn it) https://youtu.be/wOTFGRSUQ6Q
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Chapters:
00:00 – Intro: What is Machine Learning?
00:59 – Supervised Learning
01:37 – Unsupervised Learning
02:20 – Linear Regression
04:04 – Logistic Regression
04:53 – K Nearest Neighbors (KNN)
06:10 – Support Vector Machine (SVM)
07:51 – Naive Bayes Classifier
08:37 – Decision Trees
09:11 – Ensemble Algorithms
09:24 – Bagging & Random Forests
09:53 – Boosting & Strong Learners
10:26 – Neural Networks / Deep Learning
12:42 – Unsupervised Learning (again)
12:57 – Clustering / K-means
14:35 – Dimensionality Reduction
15:15 – Principal Component Analysis (PCA)
source
50 Comments
@gunhatornie · November 3, 2026 at 11:58 am
Enreejthursday
@ProgramingN-xs8ro · November 3, 2026 at 11:58 am
This video is beyond the scope
@Neonb88 · November 3, 2026 at 11:58 am
Ah, a good reminder: bagging is the technical jargon for parallel ensemble modeling, and boosting is series (for Decision Trees, in this video)
This video is great! Definitely a better fit for a broad introduction for newbies or a reminder review for folks who have taken ML before
@EVSPRAKASH-p5r · November 3, 2026 at 11:58 am
https://youtube.com/shorts/hmw9_Ld9_aQ?si=CDZnJQN8lwFVmF-i
@mhmdnayef710 · November 3, 2026 at 11:58 am
That was so awesome 👌 👏 👍, keep going 🎉🎉🎉
@SomuPujari-u3v · November 3, 2026 at 11:58 am
The idea is really helpful I will definitely recommend this.
@JayantiB-y9g8f · November 3, 2026 at 11:58 am
The production quality is underrated It deserves more views.
@DefoltLabs · November 3, 2026 at 11:58 am
I may not remeber everything said but i got the general concept the build up towards these algorithims and the examples helped me map things out. Great work. you have my sub
@heraabluess · November 3, 2026 at 11:58 am
i am really adicted to ur way of teaching sir….great video btw
@UpGrade-h2r · November 3, 2026 at 11:58 am
AI Algorithms:
Classification, Optimization, Regression, and Clustering
AI algorithms are methods used to help computers learn from data, make predictions, discover patterns, or find the best possible solution to a problem. Classification, regression, clustering, and optimization are four important algorithmic approaches.
How They Can Work Together
These approaches are often combined in real AI systems.
For example, an online store could:
1. Use clustering to segment customers.
2. Use classification to predict which customers may stop buying.
3. Use regression to estimate how much each customer may spend.
4. Use optimization to decide which promotion should be offered to each customer.
Another example is autonomous driving:
• Classification: Identify pedestrians, cars, and traffic signs
• Regression: Estimate distance and speed
• Clustering: Group sensor data or identify road structures
• Optimization: Select the safest and fastest driving path
Summary
• Classification predicts categories.
• Regression predicts numerical values.
• Clustering discovers hidden groups.
• Optimization finds the best possible decision under specific objectives and constraints.
Together, these algorithms form a foundation for many AI applications, including healthcare, finance, marketing, robotics, transportation, cybersecurity, and natural language processing.
@shauryajoshi797 · November 3, 2026 at 11:58 am
8:19 HELL NAAH
@Cloveslearning · November 3, 2026 at 11:58 am
This is a great video!!! Especially if u already know some of the methods but want to have a better image.
@Niranjan-i3n7p · November 3, 2026 at 11:58 am
bro, be little slow. you are running like nothjng
@MrJ691 · November 3, 2026 at 11:58 am
Linear regression is just a statistical model…
@asharafkaradpulikkalakath9339 · November 3, 2026 at 11:58 am
Good class
@a2kingdom764 · November 3, 2026 at 11:58 am
8:16 wild example
@sanika2889 · November 3, 2026 at 11:58 am
Oh my god , i learned more from this video than i have in the last three months😳🤨🧐
@swapnilgupta2707 · November 3, 2026 at 11:58 am
Hidden layer is dangerous
@mamun001 · November 3, 2026 at 11:58 am
Thank you
@RealNullType · November 3, 2026 at 11:58 am
I like your Naive Bayes data
@mariuszantal · November 3, 2026 at 11:58 am
yeah, science mr white!!!
@Adrian-gp6eb · November 3, 2026 at 11:58 am
What a great video!!! Thank you so much.
Im just wondering if you habe any ressources you would recommend that contain such graphics and intuitive exexplanations and visualizations
@alialasif6213 · November 3, 2026 at 11:58 am
Great video for reviewing about machine learning models
If you want a review of how much you have learn then this video is perfect, as for me I know most of the model and I understand them but if I was new then it would be problem.
@uneverknow8154 · November 3, 2026 at 11:58 am
This is AI making video about AI commented by AI accounts
@erickgave23 · November 3, 2026 at 11:58 am
Gracias por el aporte, pero hay veces que aceleras el audio, por fas no lo hagas por fas me cuesta un poco seguir el ritmo y gracias 🙌🏼
@chizoromugochi1843 · November 3, 2026 at 11:58 am
Thank you for the video.
@akma2501 · November 3, 2026 at 11:58 am
aa)) does it learn only to differentiate cat from dog or can it also learn the names cat and dog, resp.
bb)) the cat or dog it learns is exact or approximate ?
cc)) once fully learned, could it get confused if it sees a slightly different cat or dog in future ?
dd)) can it also learn from exact definitions, if a mathematically exact definition of cat or dog is given to it, without having to go through a long learning stage ?
@shazmunchdylbertoid · November 3, 2026 at 11:58 am
of course, k for knumber. obviously 😂
@tomkavings7307 · November 3, 2026 at 11:58 am
This video is the best explanation ive heard!
@kuran649 · November 3, 2026 at 11:58 am
Spam and diagram at 8:15😂
@JustCuRtZ · November 3, 2026 at 11:58 am
Great content clear, informative, and kept me interested from start to finish
@preetirawat-i6e1y · November 3, 2026 at 11:58 am
For anyone who wants a more detailed explanation, I cover many of these concepts in my book, Deep Learning: From Curiosity to Mastery.
@Yuhisern · November 3, 2026 at 11:58 am
Im suffering to understand everything by heart …
@sm-pz8er · November 3, 2026 at 11:58 am
Loved the video, the visualization and explanation. Thank you
@SurajKumar-rl7cn · November 3, 2026 at 11:58 am
Wait, so those complex neural networks are actually just fancy versions of simple line graphs? I saw a lesson on this when trying the AI Course Autopilot on Doitong AI, but hearing him say they're the same thing still confuses me.
@MsSoapify · November 3, 2026 at 11:58 am
This video is not helpful to beginners, its more of a refresher for people who have already learned some basic statistics. The speaker is kinda just reading off a script, but its not going to give you a very intuitive sense of all these concepts. You will need to have heard most of these terms before
@Nuketyzen · November 3, 2026 at 11:58 am
Might be the only utube video where I decreased playback speed instead of increasing it
@prakashraja2288 · November 3, 2026 at 11:58 am
A nice summary. Are you doing PhD or already one in ML.and DL ? If not, why are many data scientists wanting to do phd and then go via applied scientist or research scientist route as career path ?
@LegoManGonzalez20 · November 3, 2026 at 11:58 am
Im glad I could recognize most of the ones on the tumbnail, I've been learning so much
@DadBod-y1y · November 3, 2026 at 11:58 am
What about Lightgbm??? How is it different from XGboost?? Is it really better for more stats?
@Kids_Cartoon_Bangla_bn · November 3, 2026 at 11:58 am
I might need a day off to finish this video 🙂
@amrut_05 · November 3, 2026 at 11:58 am
This might be first video where i dont need to play it on 2x , rather I reduced the speed by -0.25
@paulostout · November 3, 2026 at 11:58 am
YOU ARE A LEGEND. I have my final year AI test tomo and this has been super helpful. Thank you.
@rahil6455 · November 3, 2026 at 11:58 am
Have an exam in 2 hours, this was a great recap cheers
@UTube-g3i · November 3, 2026 at 11:58 am
Penis 😂
@Maeve-Codes · November 3, 2026 at 11:58 am
Love how the things that I actually need to know for the exam aren't in the scope of this video…
@Mathematics_N-io4yy · November 3, 2026 at 11:58 am
wow i have learn a lot
@ahmadfawzilafi · November 3, 2026 at 11:58 am
amazing
@Sgaming-ex6ws · November 3, 2026 at 11:58 am
Thank you thank you…..
@Pedritox0953 · November 3, 2026 at 11:58 am
Great video! Peace out