Neural Networks Part 8: Image Classification with Convolutional Neural Networks (CNNs)
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- Опубліковано 15 чер 2024
- One of the coolest things that Neural Networks can do is classify images, and this is often done with a type of Neural Network called a Convolutional Neural Network (or CNN for short). In this StatQuest, we walk through how Convolutional Neural Networks work, one step at a time, and highlight the main ideas behind filters and pooling.
NOTE: This StatQuest assumes that you are already familiar with...
The main ideas behind neural networks: • The Essential Main Ide...
The main ideas behind backpropagation: • Neural Networks Pt. 2:...
Neural networks with multiple inputs and outputs: • Neural Networks Pt. 4:...
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0:00 Awesome song and introduction
1:51 Image classification with a normal Neural Network
4:28 The main ideas of Convolutional Neural Networks
4:59 Creating a Feature Map with a Filter
7:58 Pooling
9:48 Using the Pooled values as input for a Neural Network
11:29 Classifying an image of the letter "X"
13:04 Classifying a shifted image of the letter "X"
#StatQuest #NeuralNetworks #Convolution
Learn how to code a simple Convolutional Neural Network with this fully annotated Jupyter Notebook: lightning.ai/lightning-ai/studios/build-train-and-use-a-convolutional-neural-network
The full Neural Networks playlist, from the basics to deep learning, is here: ua-cam.com/video/CqOfi41LfDw/v-deo.html
Support StatQuest by buying my book The StatQuest Illustrated Guide to Machine Learning or a Study Guide or Merch!!! statquest.org/statquest-store/
Great playlist! Can you also make a video on variational autoencoder networks?
@@evelinewuytens2890 I'll keep that in mind.
Hey josh, is that possible to make videos about rcnn, fast rcnn, faster cnn & yolo
I watched some videos and read some paper, didnt clear explain math part(only understand basic concept)
Especially how to caculate selective search, how to train(one image contain many classification, how to train when we have many many images)
@@bennybenbenw I'll keep those topics in mind.
I can't imagine how much time and effort you put for:
1. Creating the content and simplifying it for us
2. Create the animated ppts
3. Explaining every step with great detail and simplicity
I just wanna give a huge hug to you sir! You are an asset. ❤❤
Wow, thanks!
@@statquest for real! This is amazing! Thank you so much
4. Writing the song lines and adding attractive music to them to add some entertainment to the whole matter
As a Cambridge qualified PhD Mathematician, I cannot begin to describe how fantastic your series are. The way you simplify the concepts, yet keep true to the underlying Mathematics is quite amazing. Not to mention the great animations, dynamic graphs and equations, etc. Well done Josh, for making principled data science accessible to the general audience.
Wow! Thank you very much!
As a person with a PhD in Subjective Applied Mathematics from the University of American Samoa, I approve this message
Josh needs to be on brilliant,can you guys help
You saved my life. The best CNN explanation I've ever seen
Hooray!
why did it save you? do u have Neural Network homework or what?
Just wanted you to know that I'm earning my bread and butter just because of you. Thank you teacher!
Congratulations! BAM! :)
Amazing work. I'm started learning DS and I can't imagine how I can handle all of this information without your videos. Big thanks for everything you've done, do and will do
Thank you very much! :)
I was a undergrad poli-sci data analytics student three years ago. I couldn't imagine myself going into data science because I know I am not a STEM student nor do I have a great working brain for math. But when I watched your videos back then, I was able to get confidence that I can give myself a chance to study DS which I love. Here, three years later, I am in the MSDS program at Columbia University studying data science. This was only possible because of your ml/stats videos. I still find myself studying your videos to understand concepts, which allows me to read the text without spending countless days stuck. I sincerely thank you very much for giving me a chance to actually dive on such a complex but cool subject.
WOW!!! Congratulations!!! That is awesome. It's an honor to be a small part of your success and it motivates me to do more. Thank you!
I can't stop thanking you for your content! I am a master in data science student and usually before engaging with the commonly unfathomable statistical learning books I come to your channel to grasp the topics.
BAM! :)
BEST CNN VIDEO IN THE INTERNET
bam! :)
Eagerly waiting for LSTM and it's varients. awesom explaination ...
Noted
@@statquest And GRU, please!
Just to let you know how much I appreciate your quests! Absolutely simple but not missing any concept
Thank you! :)
"I don't know how much time does Artificial Neural Networks take to train, learn the input data, But you are putting more efforts and it taking much time in your training time".Thanks to your efforts sir.
, your videos really explains very well and it helps us in visualizing easily.
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You are a gift of God to the education of Machine Learning!!!! Thank you so much!!
Thank you!
I've never seen such a simple yet very good explanation of a CNN. Thanks a lot! As a non-native english speaker I really love the simplicity and the written texts in your videos.
Thank you!
I don't know how can I thank you for pouring such knowledge to us for free.
Thanks!
This is the best explanation for CNN I have ever come across. I am very sure this is best I will ever see. I cannot you thank you enough. I have had explanations from my instructors who are PhD, MTechs and what not!! even they could not explain why filters are able to extract features and why we use global pooling. The answer I got was to reduce the number of inputs nodes to NN (which is partly true also) but the way you have explained the importance of pooling, I was amazed and equally happy to see. Thank You Josh Sir. I think you should be knighted for your efforts 😃👏🏻👏🏻👏🏻👏🏻👏🏻
Thank you! :)
Sir Josh Starmer first of his name ,the ruler of StatQuest realm 🙏
@@liviumircea6905 Ha! you made me laugh. :)
Everytime I see a new video from you I feel like I got a GOLD coin for free. Thank you Sir!
Awesome!!!
Never seen easier version of neural network! whole neural network series is a blessing. A BIG THANKS!
Thank you very much! :)
Oh my goodness! this is the simplest way CNN has ever been explained while still keeping true to the Maths. Thanks so much, Josh!
Glad you liked it! :)
I literally binged your neural network videos in a day like a Netflix show and now realized that I am at the end of the series to date and I need to wait for a new episode!
BAM! :)
This is one of the best explanations of CNNs I have ever seen!! You’re a gifted teacher man! Thanks for the refresher!
Wow, thanks!
This is the best explanation i've checked to many resources but no one simplified that much!
Thank you!
After watching the unskippable lectures of my professor for hours and understanding nothing, this 15 min viode did wonders, thanks Josh! 😌
Glad it helped!
What a simple way to explain such a complex topic. Perfect explanation Josh.
Thank you very much! :)
@@statquest Thank you so much for making these amazing videos for us Josh. I hope in the near future we get to see how RNN's with LSTM work :)))
Came for this video, ended watching half of the series. Just learned this last week in deep learning and wanted to repeat everything neat and nice, thank you very much!
Glad it was helpful!
Best playlist on neural networks i've ever seen. Thanks for this effort.
Wow, thanks!
You are an amazing teacher -- we're lucky to have you.
Thank you!
Hi Josh. Thank you so much for these videos. All videos you do are fun and so easy to understand. Without any doubt when I see your explanations I can conclude that things are not difficult, they are just badly explained. Your explanations are fantastic. I decided to support you. I am sorry I cannot provide the amount you deserve for such a quality education, but I am merely a student. However, I will not forget you when my condition improves. Please do not stop helping us.
Wow! Thank you very much! It means a lot to me that you care enough to contribute. :)
Seriously!!!!! you are the best among Tech content creators .... always love the way you explain things ....
Thank you! :)
I can't imagine how you can explain so simply ...hats off to your work ..great and superb explanation...need lot of statistical videos like this
Thank you so much 😀
i love your little musical jingles at the beginning. thank you so much for sharing your knowledge in such a fun way. Youre the goat
Thanks so much!
Thank you Josh! It is so amazing you explained CNN clearly in just 15 minutes :)
BAM! :)
I was really confused on this concept before I came across this video, now I feel I understand it way better. You really helped a lot! Thank you so much!
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Hands down to the best video and great channel. Thank you for the incredible effort and dedication!
Thank you very much! :)
Abicim yemin ederim hayatımda bu kadar iyi anlatım gördüğümü sanmıyorum
Bam! :)
Hey Josh! Thank you so much for this video. This is the best CNN Explanations I have ever seen.
Thank you very much! :)
Please consider doing an NLP series from regression to bert
I'll keep that in mind.
I think transformer and self-attention is a very hard topic for explain, so let him some time.
@@buithanhlam3726 True. It was just a suggestion for the future.
@@xiaoqingwan1912 noted! :)
I third that! Would love to see an NLP series.
Just finished the NN series. If only my highly-cited professor could explain as clearly as you could.
Thank you
bam! I'm glad you like my videos.
Thanks for the video! I watched (and took notes) of the whole Neural Network series :) Like others have said: you explain difficult concepts in such an elegant simple way, while staying true to the basic mechanisms of the concept.
Awesome, thank you! And thanks for your support!
GOAT video. What a great simple, relaxed way of explaining things. Cheers!
Thank you!
Thankyou. Thankyou! You are amazing master of explaining things... break it down to the smallest chunk and and build it up in step by step. I very much look forward for more marching learning tutorial. There is lot of tutorial out there and I spend lot of time understanding it but nothing match the the way you explain. Thank you Tons for awesome contents you have created and the insights you provide
Glad it helped!
I've watched a lot of statquest videos but I think this is my new favourite!
bam!
Thank you Josh!!! You truly are the best at explaining these concepts. I would love to see future videos on how to train the kernels, and more on image recognition/computer vision (clearly explained of course). I also got your book and it's really nice, maybe there can be a part 2 in the future 👀
I'm writing a new book all about neural networks right now and hope to have it done soon.
omg you guys are so amazing, really explain very complicated concepts in a clear, quick as well as funny way!!!
Glad you think so!
Thank you very much for the explanation! The best explanation i've ever had on CNN, made me wanted to watch the entire neural network series
Glad you enjoyed it!
Amazing video! As always, I am incredibly thankful for all the time an effort you put on to these lessons :)
Thank you! :)
Me searching any ML topic on youtube; Convolutional neural network Statquest. Thanks for the great explanation.
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You are unbelievable man , lots of respect for you to putting a lot of efforts to make things easy for us. Thank you so much ❤
Thank you!
What professors try to explain for weeks can u explain in 15 minutes.
Thank you man
Thanks!
This is the best neural network layers explained in the entire video community
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I am speechless, of your work and how you achieved your teaching intention, at least in my case, I would say that this explanation is PERFECT, I havent watched a lot of youtube friendly explaining videos on CNNs but surely this one is perfect, dont need to see another one🎉
I'm glad you like this video! :)
The best explanation I've ever seen of a CNN.
Thank you! :)
Hey, Thanks for the simplified explanation.... it's too good!!
Thank you! :)
You're literally a saint for this content! Thank you very much.
Thank you!
Your videos have inspired me a lot when I was a master student in data science. And now when I go further as a PhD student, your video is still inspiring me!!!! Many thanks for your videos!!! pls go further and further
Thanks and will do! :)
You explain things VERY well. Thank you very much ! The colors really help.
Thank you! :)
Thanks for the awesome content, just loved this neural networks series!
Thank you very much! And thank you for your support!!! :)
so clear explanation. Thank you so much for this lecture.
Glad it was helpful!
The best tutorial as always. Thanks. Looking forward to seeing RNN.
Glad you enjoyed it!
Bro you're carrying me through my ML course and exam
Good luck! :)
wow, you're the best at explaining's things for easy understanding. "Simply Great"
Wow, thanks!
simply an amazing explanation.
Thank you!
Wow, that was the best explanation of CNN. Looking forward to RNN explanation made so succinct and to the point. Thanks a lot!
Thank you very much! :)
This series is the best thing that happened to me before my Deep Learning exam lol. Everything is explained in such a simple and fun matter and it made me actually enjoy learning these concepts and makes me want to learn even more about the subject.
Good luck on the exam! BAM! :)
@@statquest now that i've been blessed with the famous BAM i think i really will have good luck :D thank you!!
@@octavia7530 :)
I saw the entire NN series. Thank yoy Josh! BIG BAM!!
Thank you!
This is my favorite video so far! I not so familiar with math but I want to learn all this stuff because I love science and I need this background and your videos have made my journey not just easier but possible! Thank you so much!
Glad it was helpful!
All of your videos are amazing. You are very talented to explain complicated things in a simple way. I am looking forward to seeing embedding, attention and transformers videos from your point of view.
Awesome, thank you!
BAM best explanation with amazing well thought example to follow, I can't thank you enough!
Glad it was helpful!
Hello josh, without you, my journey in data science wouldn't be this easier.
Thanks!
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Wow!
What an explanation!
Thank you so much for all these wonderful contents.
Keep it up! 🎉
Thank you!
Thank you for helping me and my friends in our journey
Thanks!
more video for NLP please!!! cannot say how much I enjoy watching your videos!
Glad you like them!
you are a LEGEND, this saved me probably days. thank you so much
Thanks!
Excelent! That was awesome! Very easy to understand. Thanks!
bam!
Best explanation ever! Thanks a lot.
Glad it was helpful!
that was awesome. thanks very much Josh. big shout out from brazil
Glad you liked it! Oi Brasil!
Thank you very much you are saving my master's degree
Good luck!
These lessons must be really cool to do. Just seeing the model work for a shifter X must be an fantastic experience
Thank you!
Huge thanks to you! Can't believe I can learn this for free.
bam! :)
THIS IS AMAZING, Josh. Thank you so much. now I understand the concept.
Thanks!
I just finished the quest, it was so informative, thank you so much. will use this information in my research
Thank you!
Awesome explanation. Thank you so much.
Thanks!
Thank you, this was sooo helpful ! Best video to explain CNN
Thank you!
thank you for all this amazing work that you do!
Glad you enjoy it!
Thanks for the simple and concise explanation. Just got your book off of gumroad and looking forward to diving in
Awesome, thank you!
This has been so lovely. 'bout to dive into a data science intensive and this has excited and intimidated me.
I hope it hasn't intimidated you too much. Really, if you are comfortable with The Chain Rule ( ua-cam.com/video/wl1myxrtQHQ/v-deo.html ) and Gradient Descent ( ua-cam.com/video/sDv4f4s2SB8/v-deo.html ), then the topics should not be too hard.
I am watching this a day before my exam and i don't even know how to thank you ! i am a big fan of your work (double bam)!
Good luck!!! :)
Very good video! You are a live-saver. Thanks
Glad it helped!
I passed my exam by your video )))) thank you ))
Congratulations!!! TRIPLE BAM! :)
Excellent video, To the point and complete description. I was actually looking for a good course on NN. I will use the playlist provided in the channel
Awesome, thank you!
This video is so awesome!!!!!! It made my CNN concepts crystal clear❤
Mega bam💥
Thank you!
As always, your videos are fresh as air
Thanks!
Thanks Josh! Great summary of the method
Thanks!
fantastic explanation!
Thank you!
Commenting for the algorithm. You post great videos!
Thank you very much! :)
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Thank you!
i'm reading François Chollet's book and whenever i need visualization or i'm stuck i come to your channel, great work.
Thank you! :)
Thank you a lot!! Your videos are the best!!
Glad you like them!