Learning To See [Part 15: Information]
Вставка
- Опубліковано 14 кві 2017
- In this series, we'll explore the complex landscape of machine learning and artificial intelligence through one example from the field of computer vision: using a decision tree to count the number of fingers in an image. It's gonna be crazy.
Supporting Code: github.com/stephencwelch/Lear...
welchlabs.com
@welchlabs - Наука та технологія
I just finished and remarked to my colleague, "possibly the best set of ML videos I've seen, since the 4 years I've been studying the subject". Great production value, but more importantly, deep understanding and explanation. Best place to start to understand decision trees. ✌️
Awesome, thank you!
This Series was amazing. Thank you very much!
Ralf Schmelcher +1
Okay, that fake paper though. I paused on it and it is a gold read.
"Welch-Wocka-Flocka upper bound" XD
And wonderful series. I love these and can't wait to see what you do next. :)
I hope this gets to the top. It's diamond!
Are you saying that something written by a guy named McScienceface is false?
"Below, drawing from information theory, rare bird mating patterns, and quantum sub-particle modeling..."
That's how you know it's gotta be right.
I don't know how did I find this channel but I am very pleased that I did.
Thank you UA-cam.
Wow... that final summary was crafted with perfection.
Thanks for another insightful series!
Thanks for watching! The editing for that final summary took soooo long, I'm glad you enjoyed it!
Ended exactly 1 year after it began. Great series!
LectiOpi wait, what? This series began 1 year ago?!? But it feels like yesterday that he started talking about it!!!!
I guess time does fly when you're having fun.
I guess I shouldn't feel so bad for not keeping track towards the end.
* slow clap, turning into standing ovation *
this series was very well done. thank you so much for creating it!
i also enjoyed the imaginary numbers one, but i think you've even improved on that!
Wow, thanks!
"Potato Farming"
"ok, just kidding on that one"
"good job paying attention"
He got me good
That summary at the end somehow feels like watching a puppy grow up... Beautiful.
I never knew anything about machine learning. Now I learned enough to first reproduce this example of finger detection, and soon hopefully my own small machine learning project.
Thank you so much, this was invalueable!
Awesome! Thanks for watching!
I've been returning to this, well made, video 4 times now.
Thank you. I've enjoyed taking this journey with you.
Incredibly well done. This is how education should look like.
Dude, so glad I found this series after it was finished. I wouldn’t be able to wait for the next video.
I loved this and all the other series you've done. Thank you for sharing this great work!!!
You're an awesome presenter! Thanks for taking me on a journey I never gonna leave...
Machine Learning is one of the most beautiful things in Computer Science!
As a student wanting to go into the field this has been an incredibly informative and inspiring series.
Thank you for all your hard work!
Awesome, thanks for watching!
Found this channel from 3Blue1Brown, clicked on this playlist, watched it all, subbed. This playlist was outstanding.
Thanks for watching! 3Blue1Brown = awesome.
just watched the whole series in a sit. amazing job, man
Marvels on Mars -- More like Marvels on UA-cam! Incredible Series, I've been hyped for every new episode. All your visualizations are so helpful. While I can't, of course, gain a deep understanding from 15 UA-cam videos, this is series has been a perfect introduction and sneak peek into what's to come in college.
Btw, I loved to listen to Language again during to concluding reflection of the whole series, it really tied everything together! Well done :)
Awesome, thanks for watching!
Thanks for introducing me to learning theory :) This series was PHENOMENAL. Seriously - your videos will live on for ages. Thanks so much for your time.
Great, another youtube channel to be hooked up on.
Amazing videos.
Bravo! Thanks for bringing the series!
One of the best series I've ever seen. Conglaturations.
Thank you!
Amazing! I have no words to describe your hard work and the beauty of this video series. Thank you so much.
Thanks for watching!
This series is way too underrated. Thank you so much. Also, impressive paper at 7:53.
Incredibly well explained. Thank you!
Just wanted to come here and say a big thank you for all your videos!
Thanks Daniel!
Thank you for such an incredible series on such a complicated topic. I look forward to more and more lessons you produce. your content is wonderful.
This is the most amazing series I have watched on the entire internet.
Fabulous.
Thank you for putting in the hard work to bring this valuable content to all the viewers.
This is the best learning material on the ML basics, not easy concept for beginners, but you made easier.
Thanks for the series. It is amazing to remember/recover it.
Amazing. You made us travel through all computer science, hahaha. It was AMAZING. Thanks a lot for this. Profound! Heuristics, variance, biases, oh my god, great series! I love the way you explain things--choosing not to diminish mathematical explanations because the underlying math offers deep insights. Excellent series!
Thanks for watching!
never knew so much things goes behind machine learning truly enjoyed the series although didn't fully understand the last few episodes but its okay still got the gist of it thanks for the series do continue my favorite one was your imaginary numbers series please do more series math thanks
Hey! I just wanted to say thank you for this series.
Your work was really remarkable and inspiring.
Hope to see more videos coming soon!
Hey Fabio, thanks for watching + commenting!
Having gone through your videos on Learning to See, I have come to the conclusion that what I have learned in college 30 years ago is definitely obsolete. I am not sad I did not pursue the AI field after 1994 and am now entering it again with Deep Learning and Reinforced Learning. Thank you for giving me new insight that I might not pickup from reading books.
Thanks for watching!
This is gold....really enjoyed the series.....best one for a beginner machine learning guy...thank u so much
Absolutely amazing videos. Just brilliant!
Wow amazing series! - Your channel deserves so much more subs..
Damn this series was so good. Please do more for KNN, SVMs, peceptrons, and deep learning!
What a quality series!
I am working in signal processing field, and never in machine learning yet.
You provided me the best introduction, I could have.
I love the fact that you treat how researchers ended with this kind of solutions.
Cheers for all you series,
Thank you!
Excellent work, congratulations on organising the content so efficiently and presenting it in such a straightforward and intuitive manner
I was lost for the last 6 episodes, but this one got me on track
Thanks for the good adventure in machine learning.
finally, we can identify fingers pretty well !!! I never knew that is so complicated and require that much effort! and you succeed! that's amazing !!
but as usual, nobody will notice my comments as this series had received too many compliments !!!
Thanks for watching and for the kind words!
Outstanding job, you definitively deserve more subscribers! Now that I understand the basics of AI, I just need to figure out how to code it all...
Excellent Series, but I must point out two Errors that appear in Minute 6:20 in this Video:
1- The Operation for Right Entropy is the Same that the Operation for Left Entropy, although their Results are different.
2- The Operation for p0 Entropy yields 0.29 not 0.97, the Operation for pl Entropy yields 0.28 not 0.92, and the Operation for pr Entropy should yield 0.3 not 1.0.
Besides I would like to make a Contribution to improve the General Understanding of the Series, I noted that You used the "+" and "-" Symbols in Previous Episodes to indicate when a Rule classified an training Data as Part of a Finger or not, also in the Toy Problem when a given Rule classified the Example Data as a Positive Example or not, but used the same Symbols to indicate in the Classification Tree when a Pixel was 1 or 0, with "+" and "-" respectively, this could lead to Confusion in my Opinion, since One could think the Tree is doing a Classification of Positive and Negative Data in each Node, when It is not the Case.
This series was so great and informative. I also just noticed that oh my god! This episode has come out exactly one year after the last one down to the day. Very good planning that is.
Wish I could say I planned that, just a happy accident though.
Very good ending, this video made my day, thank you sir!!!
wow! I love your videos. now I will have to re-watch them from #1, to get it all together :)))
Wonderful approach, I so appreciate you taking time exploring different "wrong" solutions, instead of just giving "the answer". Thanks!
Awesome, thanks for watching!
Thank you for this amazing series. Absolutely awesome!
And now to watch them all again from the beginning! :))
You know what... you've inspired me. I think I'll do my EPQ on machine learning!
Thanks for the great videos, keep up the good work!
Awesome, good luck!
Loved every bit of this series, thank you for all the effort and knowledge put into it ^^
very interesting series and thanks a lot for taking the time to make it!
WOW, Thank you so much for this amazing series!
you are amazing!
Thank you for creating this fantastic series of videos.
Thank you for this good introduction into some of the science behind AI!
Maybe I will watch the whole series again tomorrow. Hopefully that helps to understand it better.
This was the most amazing series ever! Thank you very much for this
Very well done! I hope you plan to continue releasing such quality content.
Amazing series. Can't wait for more like it.
Excellent channel and fantastic series. Thanks.
Fantastic work. Thank you!!!
What an awesome series! Thank you
Such an amazing series, had to rewatch it after the Veritasium video.
such a satisfying conclusion. love it :)
never clicked a vid so fast
me too!!!!!! we know that!!!!!!!!!!!
I've got the same feeling, bro!
a amazing journey ended just now :D Thank you for your work man!
Absolutely incredible series. Thank you for making this! If you had a Patreon I'd definitely contribute.
Amazing work.
This a very very good series on Machine Learning for beginners.
GOOD JOB.
Thanks!
Background music makes if feel easy and inspiring, although it's complicated :D
It was great to watch whole series :) I really like your way of teaching!
Awesome, thanks for watching!
Excellent series. Thank you
Great series. Thank you very much!
Wow. I almost cried 😭
Anyway...
Why doesn’t this channel have a billion subscribers already!!!???
I Love It! Great way to end it. It was fantastic
Absolutely amazing. I was wondering if you have any additional content recommendation for those of us who want to go further, but still without getting too technical (your series has been brilliant in this matter). For example: I would be delighted to better understand how google photos goes from identifying fingers in gray scale (the point in which we ended here) to identifying more complex things in a totally "open environment" (i.e., an environment in which things can - at first - be anything, not just fingers, so that the algorithm can not be prepared for any specific task such as "identifying fingers" at the beginning of the process). Do you think it is even possible to understand that in a non-technical (or "softly-technical") way? If so, where could we go for it? Thanks a lot in advance, and thank you for this great series!
deserves a standing ovation
Great way to tie everything together!
Great series, keep up with the wonderful work
amazing, you're an inspiration for my science channel. One day I hope to be able to explain like you. Here in Brazil people only memorize, the Feynman quote you had a few videos ago in this series is 100% true.
Awesome! Thanks for watching - best of luck!
Awesome. Well explained. Well done.
Watching this again 3 years later. Still a wonderful series.
This series is incredible. Thank you!
Thanks for watching!
I'm so sad you stopped making videos. I just learned machine learning this semester. I'm incredibly interested in the subject, your serie inspired me to purse it
A true knowledge is that which can change the world.
You and 3b1b are filled with it
This was an amazing video series, thanks a lot for making this, i realy enjoyed it
wow. Just wow
you did this series soo awesome. you are the first chanel i activated the notifications.
I can't wait for your next series! keep up ur good work :)
Thanks for watching!
how could I miss on such awesome content! Eventho the videos were spaced apart kinda far I still enjoied watching them all. Your recaps made it sometimes "boring" when I have watched 2 videos in a row or more, however when watching one once a month this was perfectly fine. All in all a really enjoiable chanel and very nice content!
Awesome series. Thank you.
i loved this series! thank you!!
Damn, great, as always! Do something with signals, please!
Damn I got scared by the beggining :D "LAAST time..." anyway, this series is gold!
Ok the video quality is really good but wow!! You explanations are even better! Congratulations I really like this playlist!
Thanks for watching!
Loved it! Keep up up the good work
thanks for the series, im entering college to study math and want to work with machine learning. your videos are true inspiration.
Thank you!
Excellent series!
what an amazing series it was. Thank you again!!
Thanks for watching!
Wow, it's just amazing !!!
I'm a med student, watched the whole serie .. And the last episodes flew over my head .. But it was fun
Good work keep them coming!
Amazing and informative
Thanks your very much. Muchas gracias amigo!!!