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.
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:)
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.
@@MachineLearningWithJay hey buddy, great video. please make video on TFOD installation in local system for object detection as I haven't found any specific video on TH-cam
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 🔥🔥😍😍
Heyy… yess I am from SVNIT and I shot the video from Swami Bhavan! Good to see you!! Hope your hostel life is going great!! Enjoyy it to the best, keeping the CG up to the mark!!
Super useful tutorial! But i tried to use the code for a different database and was not working, maybe show on a next video how we can work with our own databases.
@@iuliaioana4480 The same model will work for any dataset, but you might need to preprocess the data, and change your mode dims to fit on that dataset. I will keep this in mind and will cover these things in upcoming videos
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?
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
@@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!
Hello, your video did help me a lot. Thank you so much. But its was possible only because of the dataset which you have provided. Kindly guide on how to have such datasets for different classification?
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?
I want to train a model that will predict if the person has glaucoma or not Like you're doing classification between dog and cat you will differentiate dog and cat Can i use this same model to differentiate between glaucoma negative and glaucoma positive? I badly need help please help me in this project
@@kashaf_amir Hi you can use the same model for that, if there is clear differentiable indicator in the images of glaucome negative and positive. Make sure the image dataset that you use is clean and as less noise as possible.
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...
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?
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.
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 ?
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.
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!! 🤗
I studied Neural network 3 years ago. This series helped me to revise the whole thing in 40 minutes
Glad to help!!
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.
After searching a lot I came across this video. This was very clear and easy. Thanks a lot
Happy to help 🤗
This is one of the best explanations i just finished the whole playlist thank you so much for your efforts
Glad it was valuable 😇
Wonderfully explained. Just finished watching all the 12 videos from your playlist.....
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
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:)
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!
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.
This is MUCH easier to understand than the elite university certificate program I am currently in for Deep Learning.
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
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
used this video for revision pretty good and straightforward no yapping
@@Ash-bc8vw haha… yes, Thank you!
No one can give that much amount of Explaination thank you🙏🙏🙏
man your videos are absolutely crazy good. I love your teaching style. I hope you will keep going. :)
Thank you so much! Appreciate your comment
@@MachineLearningWithJay hey buddy, great video. please make video on TFOD installation in local system for object detection as I haven't found any specific video on TH-cam
This tutorial is a game changer for me. Thank you so much
Thank you so much for your playlist, it has been so usefull for me ! I hope that you're doing well :)
Everything is simple and straightforward. keep up the good work bro!
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 🔥🔥😍😍
Simplicity at its peak ❤️🔥
Really great content bro , in simplest English as if I am listening in Hindi. Very good
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!
Hats off to the excellent explanation. Great job !!!
Saras bhanave 6 bhai tu.....gamyu ane avdyu badhu video joine.......
Thank you bhai… amen pan Gujarati j che!
This was so Helpful
Thanks for that
Sending you my Love From IRAN
you are zopper good ,now i have the understand the codes now ,very clearly
Hope your doubts that you asked got resolved! 🤗
@@MachineLearningWithJay yes 😩💗
Absolutely great, double thumbs up!
amazing series bhai!
Thanks!
To the point explanation. Well done brother❤
i enjoyed your all videos on CNN
Glad that you enjoyed!
The bg made me realize that you are from SVNIT , btw great content sir
Heyy… yess I am from SVNIT and I shot the video from Swami Bhavan! Good to see you!! Hope your hostel life is going great!! Enjoyy it to the best, keeping the CG up to the mark!!
@@MachineLearningWithJay Yess clg is almost done , last two months 😅
You r Great .. This model very Effective Thank you
Bro you are great. Respect ++
Thank you so much!
Your videos are awesome. So helpful. One stop for knowledge seeker. Can you please make videos on SVM, GMMs, Maximum Likelihood estimation as well?
Thank you so much for your fantastic video! You are truly amazing.
thank you for all these videos,clear and very helpful!
can you make also videos about few-shot learning?
Thank you so much!, you're amazing!
Haha, thanks!
Super useful tutorial! But i tried to use the code for a different database and was not working, maybe show on a next video how we can work with our own databases.
@@iuliaioana4480 The same model will work for any dataset, but you might need to preprocess the data, and change your mode dims to fit on that dataset. I will keep this in mind and will cover these things in upcoming videos
Thank you very much for this video. I request you to do videos on all machine learning algorithms.
Thank you
Found it very helpful, thanks a lotttt for creating this video sir
You’re welcome 😇
you deserve a like.
Really informative. Thankyou
sos bueno Jaimin saludos de argentina la tierra del asado y del diego
Saludos!!
Saludos!
you are amazing man
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?
Very nice thanks a lot! Please upload more videos, very helpful!
You’re welcome 😇
Please do videos on RNN also. Your videos really useful. Thank you.
Great work brother, is there any video where u have implemeted using tensor flow frame work?
Bro love you.....virtual hug from me...thank you sooo much bhai.....
In input.csv file datasets it shows "Wrong number of columns at line 6" error
excellent content
thanks a lot make more please
You’re welcome! More videos upcoming
good content in short time
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
@@MachineLearningWithJay Please provide any video or link to load cats, dogs images in folder wise for classification
great explanation bro 😇😇😇😇😇😇🤩
Thankyou bhaiya!! I got output
Do I have to divide the dataset i have into train and test at first if it isn't separated??
If you already have the training and test dataset, then the split might not be needed
Bro how did u convert all images to csv files
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
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!
Hello, your video did help me a lot. Thank you so much. But its was possible only because of the dataset which you have provided. Kindly guide on how to have such datasets for different classification?
Please make a video for low-light Image enhancement using CNN
Nice job
Thanks!
Nice explanation
Thank you!
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?
Hi, can you make a video on detecting certain 'Disease causing' image objects (e.g. Lung nodules detection for lung cancer).
What about splitting of dataset to validation, validation is required or not?
I want to train a model that will predict if the person has glaucoma or not
Like you're doing classification between dog and cat you will differentiate dog and cat
Can i use this same model to differentiate between glaucoma negative and glaucoma positive?
I badly need help please help me in this project
@@kashaf_amir Hi you can use the same model for that, if there is clear differentiable indicator in the images of glaucome negative and positive. Make sure the image dataset that you use is clean and as less noise as possible.
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...
So what we do when we want multi class output ,, which activation function we use can u explain
make playlist on NLP too..........................
@@SINDAVALAMBASAVA Okay, probably in future, can deep dive into this. Thanks for suggesting.
sir please explain how to create the datasets of images
Awesome explanation. Good work
Thank you!
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?
Thanks and God bless you. I really appreciate your video.Please can you do a video on any pretrained network with svm for classification
thanks bro , nice one
Always welcome
Hi, I found your video very educative. Can you please demonstrate how CNN can be applied on cellular network for DDoS detection
thank you so much sir
Thank you very much
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
How to use directory insted of csv file? 😊
Actual lifesaver
How about how to prepare the data
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 ?
the dataset is in numerical value how it convert to numerical and how we see
how can I use it as pedestrian detection and how to find the pedestrian data set
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!!!
bro plz make video on bidirectional CNN for image classification
Hi Thanks for the suggestion. Will try to cover this topic.
hi.. awesome video. can you put video on steganalysis coding
Thanks for the suggestion… I will see if I can make video on it
you are star my dear
Hehe! Thank you so much! Glad to help!
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
can you show the severity level of the disease using CNN multiclass model?
I've a question, have you used deep learning??
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.
Thanks 👍🏿
Your Welcome!
nice content
great tutorial brother just make one video on how to use this in django and save model
Thanks for the suggestion… will try something like this may be in the future