The full Neural Networks playlist, from the basics to deep learning, is here: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-CqOfi41LfDw.html Support StatQuest by buying my book The StatQuest Illustrated Guide to Machine Learning or a Study Guide or Merch!!! statquest.org/statquest-store/ NOTE: A lot of people ask where the values on each connection come from that we use to multiply and add to the inputs. This question is answered at 3:48 - in short, they are found using a method called Backpropagation. If you want to learn more about backpropagation, check out this video: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-IN2XmBhILt4.html
@@yashaswikulshreshtha1588 what is wrong with you? The math presented is NOT difficult, it is literally basic calculus. Yes, we do understand the math. If you are struggling with this, I recommend that you retake calculus and algebra then come back here once you have a good foundation. None of this will make sense if your math knowledge is weak.
You know you are contributing massively to the society when I look forward to your video releases just as much as I look forward to some of Marvel's blockbuster films!! :D
I am a professor in computer science, and did my dissertation on Bayesian methods in AI, and I will say that this is the best explanation of neural networks I have ever seen. It does no hand-waving, and makes no assumptions about the viewer's math skills. Coming late to the CS party in my 20s, and not being from a strong math background, I can really appreciate this approach. I will be using this video series in my Intelligent Systems class. Thank you.
Wow! Thank you very much! Since you like the video, I'll be shameless and say that you might also like...the book! I cover this and a bunch of other ML topics in The StatQuest Illustrated Guide to Machine Learning here: www.amazon.com/dp/B0BLM4TLPY
I have a pretty chill phd supervisor so wondering if i can just get away with calling them 'big fancy squiggle fitting machine' for the entirety of my thesis...
Triple BAM congratulations! I bled through this six years ago , and that took me months. Here, you condensed the concepts into 18 mins! and I still learned alot ! You are a blessing!! please keep posting more videos!
For Christ sake, this guy is brilliant! Taking something very intimidating and showing how it works is worth gold. I am embarrassed to say that I am a scientist, have been for over 20 years. We over complicate and write papers to sound smart, but really never really say anything. And good luck ever trying to reproduce those results in the paper. This is how technology and science should be taught and discussed with our peers.
People like you are shaping the future of students and people who are willing to learn. May God bless you and fulfill all your dreams. Josh you are such an amazing human being.
Actual you are one of the greatest teachers of all times ! you make the most complicated subjects look sooooo easy that I was having breakfast while watching this ... and though I understood the dreaded Neural Networks 🤣🤣 Thanks alot josh, I wish you the best ❤
I just can't express how grateful I am for these videos, you have a stunning ability to make concepts stick to my and other people's mind. You're the greatest in this field!
@@ritikyadav157 Yes, I follow that channel too. His animations are also awesome!😍 But that time I couldn't understand it well because I didn't understand the previous things that is required to understand that. That is where Statquest came as a Savior!❤️
We just enjoy learning and playing with knowledge with Josh. This is all because of his efforts, we're learning so well. Hats off to this man, spending his time spreading knowledge :D
Hello, Josh. Your videos are really helpful for my research and I like them so much. Btw, I really want to see you to explain mathematics theories and terminology behind Time Series Data Analysis, such as ARIMA, SARIMA or some other machine learning algorithms! BAM me! Thank you! (also from a model family fans, I guess you are too :)
I had tried to learn Neural Networks multiple times only to find that it gets more and more complicated due to the equations and terminologies. This is the first explanation I have come across that is so clear and concise and to the point, without going into equations, jargons. Thank you so much.
Waow! This tutorial was an amazing asset for revising my concepts. Also, I haven't seen such an amazing teacher who clarifies these messy concepts, and makes easy to understand for us. Thanks a lot Sir Jost Starmer 🙂
I’ve watched so many videos on the topic & taken some lectures; but only after watching this video was I ascended to Olympos, where no one but Gods and Titans live... Now I know, I have enough strength to wrestle with Hercules, enough wisdom to take down Zeus, enough charm to get Aphrodite.. Due to the final in 4 hours, I’m coming back to earth, but I’m not the same mortal I was 20 mins ago anymore... See you soon, Aphrobaby...
The best Neural Networks explanation i've ever seen!! I went through many and all of them were pretty hard for me to understand. Keep up the good work man, you're doing great.
Amazing, Josh! I wish you and your channel existed in my life when I was younger! I'd definitely had done different career choices with this way of looking mathematics and statistics you presented in your videos! 🇧🇷🇧🇷🇧🇷🇧🇷
people say "watch 3 blue 1 brown videos" yeah they are animated extremely well and look cool, but it was easier to understand yours, you teach much much better
These videos are just incredible. I can't imagine the effort behind each video. I'm just starting out in this and don't doubt that your channel will be one of my first options whenever I have any doubts. The simplicity and especially the way you explain it, is totally a 10. Thank you very much.
I think the novel value of this video (for me) is that it helps bridge the gap left with 3Blue1Brown's video where he intuites what the NN may be doing, but then reveals that it actually appears random and chaotic, without the sense of order we initially assumed to make sense of it. This video explains that although the particular weights and biases may appear random at first glance, it is through their summation/cancellation that an order emerges. Also, kudos for introducing a new beginner example -- I genuinely did not realise that there were other applications outside of image recognition lol (I am a beginner to this!). As in, yes it's easy for us to look at the simple data and say 'hurr durr why not just model it with a quadratic equation'; but here is a different way to derive values to fit the data on the graph. Which was new to me, so, thanks!
These videos have explained the ideas so clearly in such a simple way. They literally helped me pass my actuarial exams. A big thank you for your time and amazing work!!
The toilet paper brand idea got laughing my guts out! 🤣🤣Thank you very much! I learned a lot from you. You're so fun too, it's so enjoying to watch your videos and they're so helpful and organized! ❤
Been waiting for this topic ever since I discovered your channel a year ago. Can't wait to see the next parts!!!! Thank you, an amazing job as always :D
Really good demonstration. Can you later talk about sampling method (such as MCMC or Variation Bayes). These kind of methods are really frequently used in computational biology to solve EM problem such as in somatic variant calling and cancer heterogeneity estimation.
To be honest I was eagerly waiting for you to upload contents on neural networks....can't wait to see your explanation of optimizers used in fitting neural networks.
I'm going to present my master's degree defence next month and this video, and the ones about PCA and SVM, helped me *a lot* to break down these complicated processes into something that I can actually try and explain to the professors that will be evaluating me. Thank you SO MUCH for that!
@@statquest Just thought I'd let you know that I was approved and now have a MSc degree in biochemistry and molecular biology! Thank you very much for your help! 😃
Man if only i had discovered this channel a while back when I was having my stats and data analysis classes, I wouldn't have performed so terribly x) Good thing that I found out about it now so I still can re-learn all what I missed on, now that I need that knowledge the most. Thank you so much Mr Starmer, you and your videos are wholesome beyond belief
Josh, that was simply fantastic. I've watched a lot of videos and taken a course in NNs, and I've never seen an explanation like this. This was exactly what I was looking for. I don't know how you know what you know, or why no one else seems to be able to teach like you do, but THANK YOU!!!
Masters Student here, went for my first NLP class and didnt understand a word. After Class, started watching the series, Now I can understand what my prof says in class .. :)
Thanks Josh for helping remove the gatekeeping on Machine Learning for folks! It often is held as a this thing only prodigy's or math wizards can do, but you are helping to make it accessible for everyone! Keep up the amazing work.
Man, your tutorials are really triple BAM! I'm so appreciated for them. A small annoing remark - 16:08 if you want to get f(x) = log(1+e^x)=0.71, you should plug in x=0.03 into equation, not x=0.3, as far as at 16:05 (0.5 * -2.52) + 1.29 = 0.03. Sorry man, you're the best at the end of the day!
Josh I just wanted to say thank you very much for all this content, it's really enlightning and very powerful in a sense that just with simple and not so fancy explanations I'm able to nail down every single concept and idea. I'm currently taking a financial engineering masters degree and let me tell you that your approach has been really helping me out. Also, in form of gratitude, I bought the 'Everything Bundle' from gumroad and it's been quite an awesome experience to learn from it and sharpen some loose math and stat concepts that I had on me. Big thank you from Chile.
You made laugh, get interest and BAAMM! I'm studying a course of Machine Learning and got a profound level of stats, so I needed a couple of videos of depth and I found you. This channel is amazing, I'm gonna watch everything. You're awesome.
