Neural Networks Part 8: Image Classification with Convolutional Neural Networks (CNNs)

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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.

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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

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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. ❤❤

GeekyMan

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.

ddb

Why am I not able to stop the playlist? Why am I still not bored!?
Great effort in making things simple and fun. BAM!

shubhamraj

The Moment I Saw The first video of this series, I immediately placed an order of the book ! Cant Describe How well u are explaining. Blessed To Have Youtubers Like You .

surajsamantha

As a PhD candidate in machine learning at Harvard, I cannot stress how simple and beautiful your videos make complex concepts. Well done <3

KoffeeKlaire

You saved my life. The best CNN explanation I've ever seen

TuanLe-octe

Just wanted you to know that I'm earning my bread and butter just because of you. Thank you teacher!

sagnikbhattacharya

Ive seen multiple videos on CNN and nothing made me understand convolution, but this! Thanks statquest <3

EyMaxl

Eagerly waiting for LSTM and it's varients. awesom explaination ...

AMVSAGOs

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

dmitriykalashnikov

You are a gift of God to the education of Machine Learning!!!! Thank you so much!!

rituchaudhary

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.

grantkim

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.

davidpinedo

"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.

nikhilb

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 😃👏🏻👏🏻👏🏻👏🏻👏🏻

shamshersingh

I don't know how can I thank you for pouring such knowledge to us for free.

social.

Just to let you know how much I appreciate your quests! Absolutely simple but not missing any concept

KhoaLe-ocxl

Oh my goodness! this is the simplest way CNN has ever been explained while still keeping true to the Maths. Thanks so much, Josh!

Techdadphd

After watching the unskippable lectures of my professor for hours and understanding nothing, this 15 min viode did wonders, thanks Josh! 😌

wolfywolfgang

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.

piasophie

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