Thank you so much, brother, for this STELLAR series on CNNs. Without a doubt, the BEST on TH-cam. Your efforts do not go unnoticed. Please keep making high quality content. Cheers from Austin, Texas!
The quality of content, simplicity in the explanation, teaching from the basics, explanation of the dimensions and model architecture parameters; everything about the playlist is so amazing. Great job man!! Playlist suggestion: 1D CNN on time series data passing big window-sized data (time dimension) along with a multi-headed neural network targeting classification and regression simultaneously is something I would love to see.
Brother, this video has been an enormous help to me. I'm doing my thesis to get the Mechatronic engineering degree on DL, which is how to be a specialist in AI in postgraduate. Greetings from Mexico.
Thanks for your effort and time in creating such great content. I have completed the whole playlist and learned the fundamentals of NN. Thanks again! Keep creating, teaching and sharing:)
i watched your entire playlist its pretty amazing the way you have explained everything it went in my mind without any resistance.... thanks a lot its a great help....... You are really good at teaching keep it up 🔥🔥😍😍
just completed watching all your videos and what I feel sad about is that you are inactive since 2 years. I just want to ask is everything alright because you suddenly disappeared from TH-cam. If everything is okay then please continue with your channel as I totally love your videos and teaching style
its a great video got the concept but the predictions are not always coming right likr the dog nd cat numbers are not always coming right many times dogs values are also greater then 0.5 ...how to improve it ?
When I took regression analysis years ago, there was a way to look at residuals and outliers to see if the data might not look right for certain observations. Does deep learning have that way to inspect images to see if some don't look good enough?
Hey Bro, Loved your entire playlist! It was really helpful. I had a question though. In the end, if the probability for one of the dog images was below 0.5, does that mean that all dog images will have a probability of being less than 0.5? If no, then how are we using a fixed threshold for classification? Can it not lead to erroneous classification too?
This is really helpful.. thanks so much! But I'm unable to download the dataset completely,it's saying no access; is there another way I can get the dataset downloaded?
@@actionandentertainment5289 I will make a video, where I will show to create a full-fledge application with machine learning model at backend and an interface at the front end, but I am not planning to do it anytime sooner. If you want some help then you can checkout this project of mine on github. Its a chatbot with web interface, where you can give input and machine learning model will produce output. github.com/Jaimin09/Jessica---A-Virtual-Assistant Hope it can help you!
while fitting the model, how do we get to know that when we have to stop re-running epochs count for better accuracy? like by doing it again and again we can reach to desired accuracy level...
I don't have the link from where I collected the dataset. But you can find datasets on Kaggle. Or you can also search online for datasets. They are easily available as long as you don't require very large database.
You need to install numpy using pip or conda, whatever environment you are using. Try running the following command in your command prompt "pip install numpy" if you are using pip. Also search online about how to install numpy on your system
You are too much. Best among equal, thanks for this video. please is it possible for you to replace the fully connected layer with svm or any other machine learning algorithm. i need a video of the implementation on that, Thanks i really appreciate
Hi, yes you can try to predict objects in zoomed out images. However, the performance might decrease for zoomed out images, as there can be multiple other items in the image.
Hello Thank you for this wonderful tutorial. I just wanted to ask at 5:43 you divided all those values with 255 as I am beginner I had question like why did you divide with 255 ? It would be great if you could explain a bit. Thank you for the tutorial by the way.
Project Title - Image Recognition and Classification Description: Develop an image recognition system using convolutional neural networks (CNNs) or deep learning models to classify and recognize objects, scenes, or patterns in images for applications like image search or medical imaging. Please help me in doing this
Sorry for the late reply. You have successfully downloaded the dataset right? In that case make sure your dataset is in the same folder where your code is present. If your code is in file ImageClassification.ipynb, and is present in "mycode" folder, then mycode folder must have the following structure: mycode> ImageClassification.ipynb input.csv input_test.csv labels.csv labels_test.csv
Thank you so much, brother, for this STELLAR series on CNNs. Without a doubt, the BEST on TH-cam. Your efforts do not go unnoticed. Please keep making high quality content. Cheers from Austin, Texas!
Hey… thanks a lot for this. I really appreciate it!! 🤗
The quality of content, simplicity in the explanation, teaching from the basics, explanation of the dimensions and model architecture parameters; everything about the playlist is so amazing. Great job man!!
Playlist suggestion: 1D CNN on time series data passing big window-sized data (time dimension) along with a multi-headed neural network targeting classification and regression simultaneously is something I would love to see.
This is one of the best explanations i just finished the whole playlist thank you so much for your efforts
Glad it was valuable 😇
After searching a lot I came across this video. This was very clear and easy. Thanks a lot
Happy to help 🤗
Thank you so much for your efforts. It is the best playlist explaining CNN
Thank you so much!
Explaining everything from the basics is extremely useful...especially in deep learning.
Happy to help!
How can I get code
Maybe best explanation on YT on this topic, i am looking at hours of content and this 18 min video helped me a ton, Thank you!
The bg made me realize that you are from SVNIT , btw great content sir
gotit... I usually don't comment but this video definitely deserve a round of applause... You have explained it the best possible way. Many thanks! 🙂
Thank you so much… it means a lot to me.
Brother, this video has been an enormous help to me. I'm doing my thesis to get the Mechatronic engineering degree on DL, which is how to be a specialist in AI in postgraduate.
Greetings from Mexico.
Greetings! Glad it was helpful to you 😇
At 6:33 when i am running it i am getting black images no the image of dog or a cat how to resolve it can anyone tell
Thanks for your effort and time in creating such great content. I have completed the whole playlist and learned the fundamentals of NN. Thanks again! Keep creating, teaching and sharing:)
Bro you are great. Respect ++
Thank you so much!
Saras bhanave 6 bhai tu.....gamyu ane avdyu badhu video joine.......
Thank you bhai… amen pan Gujarati j che!
That's amazing the way you have thought all the playlist was outstanding, really helped me and cleared lots of my confusions
Respect from Afghanistan
Thank you. You are a very nice person and easy to learn these easy concepts from.
Thank you man please keep doing these kind of videos
Thank you. Will do!
Thank you so much!, you're amazing!
Haha, thanks!
i watched your entire playlist its pretty amazing the way you have explained everything it went in my mind without any resistance.... thanks a lot its a great help....... You are really good at teaching keep it up 🔥🔥😍😍
Really great content bro , in simplest English as if I am listening in Hindi. Very good
Thank you so much for your playlist, it has been so usefull for me ! I hope that you're doing well :)
sos bueno Jaimin saludos de argentina la tierra del asado y del diego
thank you for all these videos,clear and very helpful!
can you make also videos about few-shot learning?
Hats off to the excellent explanation. Great job !!!
Your videos are awesome. So helpful. One stop for knowledge seeker. Can you please make videos on SVM, GMMs, Maximum Likelihood estimation as well?
You r Great .. This model very Effective Thank you
amazing series bhai!
Thanks!
just completed watching all your videos and what I feel sad about is that you are inactive since 2 years. I just want to ask is everything alright because you suddenly disappeared from TH-cam. If everything is okay then please continue with your channel as I totally love your videos and teaching style
In input.csv file datasets it shows "Wrong number of columns at line 6" error
Really informative. Thankyou
Thank you so much for your fantastic video! You are truly amazing.
Very nice thanks a lot! Please upload more videos, very helpful!
You’re welcome 😇
you deserve a like.
its a great video got the concept but the predictions are not always coming right likr the dog nd cat numbers are not always coming right many times dogs values are also greater then 0.5 ...how to improve it ?
Hi, can you make a video on detecting certain 'Disease causing' image objects (e.g. Lung nodules detection for lung cancer).
Bro how did u convert all images to csv files
sir please explain how to create the datasets of images
Bro love you.....virtual hug from me...thank you sooo much bhai.....
how did you upload those images?
and how did you make a csv file?
please dont use shortcuts I need to know this in details help me with it asap!!!
How I can train with own images I saw image and it should tell the detail which I have trained on
excellent content
Awesome explanation. Good work
Thank you!
Please make a video for low-light Image enhancement using CNN
good content in short time
Very interesting, How about CNN IMAGE PROCESSING VIDEOS
while loading the dataset i get an error msg
you are amazing man
Nice explanation
Thank you!
Nice job
Thanks!
When I took regression analysis years ago, there was a way to look at residuals and outliers to see if the data might not look right for certain observations. Does deep learning have that way to inspect images to see if some don't look good enough?
thank you so much sir
Hey Bro,
Loved your entire playlist! It was really helpful.
I had a question though. In the end, if the probability for one of the dog images was below 0.5, does that mean that all dog images will have a probability of being less than 0.5? If no, then how are we using a fixed threshold for classification? Can it not lead to erroneous classification too?
Thank you very much
great explanation bro 😇😇😇😇😇😇🤩
you are star my dear
This is really helpful.. thanks so much!
But I'm unable to download the dataset completely,it's saying no access; is there another way I can get the dataset downloaded?
How to use directory insted of csv file? 😊
Jay, I can't download the dataset. Please help ...
bro plz make video on bidirectional CNN for image classification
Hi Thanks for the suggestion. Will try to cover this topic.
Very informative
So what we do when we want multi class output ,, which activation function we use can u explain
i want dataset dataset link is not working
Can you make a video on creating interface? after development of model
Waiting for your kind response
@@actionandentertainment5289 I will make a video, where I will show to create a full-fledge application with machine learning model at backend and an interface at the front end, but I am not planning to do it anytime sooner.
If you want some help then you can checkout this project of mine on github. Its a chatbot with web interface, where you can give input and machine learning model will produce output.
github.com/Jaimin09/Jessica---A-Virtual-Assistant
Hope it can help you!
Hi, I found your video very educative. Can you please demonstrate how CNN can be applied on cellular network for DDoS detection
while fitting the model, how do we get to know that when we have to stop re-running epochs count for better accuracy? like by doing it again and again we can reach to desired accuracy level...
Im getting graphs as the output and not the images
the dataset is in numerical value how it convert to numerical and how we see
Bro could you explain vision transformer with example and creating one transformer base image classification model from scratch
Wonderfully explained. Just finished watching all the 12 videos from your playlist.....
Hi sir, I followed you tutorial but somehow model accuracy does not change and remains at 0.5
I have same error, it stays at 0.5, I know this comment is 2 months ago, so if you did find the solution, kindly reply, it would be a great help
Thanks 👍🏿
Your Welcome!
how can I use it as pedestrian detection and how to find the pedestrian data set
Thanks
Greetings! Please show how to build CNN from scratch without using ready-made libraries No Tensor Flow, No Keras, No Pytorch
amazing
hi.. awesome video. can you put video on steganalysis coding
Thanks for the suggestion… I will see if I can make video on it
Sir can you make a video on multiclass label image classification using vision transformer
I learn so much from this video. Why you taken Image dataset in .csv format. Can we load images directly with folder labling?
Glad it helped you… and yes you can directly load the dataset as well
@@CodingLane Please provide any video or link to load cats, dogs images in folder wise for classification
I don't why I getting runtime error can anyone please help me out from this
nice content
Trying to install tensorflow becaise of user pernissions denied and path not mentioned..please help me
hey there the short link isnt working anymore cannot get a hold on the dataset
Yes… I it got deleted accidentally… I will upload it again
please tell from where u collected the dataset??... I want to collect the dataset of tree images
I don't have the link from where I collected the dataset. But you can find datasets on Kaggle. Or you can also search online for datasets. They are easily available as long as you don't require very large database.
bro when are you going to upload more videos? very helpfull
when i try to load the dtaset it says name 'np' is not defined. But i hv downloaded the dataset ald but quiet confuse on where to put the datasets
You need to install numpy using pip or conda, whatever environment you are using. Try running the following command in your command prompt "pip install numpy" if you are using pip. Also search online about how to install numpy on your system
Excellent interpretation, but I can not download the dataset. It says "This site can’t be reached". What can I do?
I've a question, have you used deep learning??
Its showing file not found while loding data set pls reply tommrow is my mini project
Hi… I will look into… thanks for letting me know… will tell you if I fix it
How do I convert a folder of images (probably each has different resolution ) into a trainable .csv file?
You are too much. Best among equal, thanks for this video. please is it possible for you to replace the fully connected layer with svm or any other machine learning algorithm. i need a video of the implementation on that, Thanks i really appreciate
You are treasure
thanks dude
please what is the code for the learning curves I need today please someone help
did you use MobileNet architecture for the CNN model?
Is this code will be useful for zooming out the images
Hi, yes you can try to predict objects in zoomed out images. However, the performance might decrease for zoomed out images, as there can be multiple other items in the image.
Hello Thank you for this wonderful tutorial. I just wanted to ask at 5:43 you divided all those values with 255 as I am beginner I had question like why did you divide with 255 ? It would be great if you could explain a bit. Thank you for the tutorial by the way.
To normalize the data values
Dataset link not opening. PLZ HELP..😭😭
usng this, can deploy to android studio for app right??
Yes we can
Project Title - Image Recognition and Classification
Description:
Develop an image recognition system using convolutional neural networks (CNNs) or deep learning models to classify and recognize objects, scenes, or patterns in images for applications like image search or medical imaging.
Please help me in doing this
I'm facing some problems is epochs and batch_size
Hi, whats the issue?
It's showing that unknown loss function. Pass object to custom_objects argument
@@Me_Sayandeep Did you follow my code properly? And you have the dataset I used or any other dataset?
@@CodingLane yes .i followed ur code ..bt use another data set
How to solve input.csv file not found
Sorry for the late reply. You have successfully downloaded the dataset right? In that case make sure your dataset is in the same folder where your code is present.
If your code is in file ImageClassification.ipynb, and is present in "mycode" folder, then mycode folder must have the following structure:
mycode>
ImageClassification.ipynb
input.csv
input_test.csv
labels.csv
labels_test.csv