Check our Deep Learning Course (in PyTorch) with Latest, Industry Relevant Content: tinyurl.com/4p9vmmds Check out our premium machine learning course with 2 Industry projects: codebasics.io/courses/machine-learning-for-data-science-beginners-to-advanced
Your tutorials are truly outstanding, surpassing many paid online courses. I want to express my deep appreciation for the invaluable support they've offered. Your detailed explanations of each code line have been incredibly helpful, particularly when I'm teaching machine learning to my students. Your videos provide a level of comprehension and utility that distinguishes them from other machine learning resources. Your efforts are greatly appreciated... Cheers!!!!!!!!!!!!!!!!💥💫💢
I am a young Ai and machine learning engineer from a IIIT and your videos are like food for me if i don't eat then I can't live .Great explanation ... finally I commented after watching tons of your videos daily . Salute to your spirit sir you will reach 10 M subs soon cause AI and ML is growing exponentially and your videos in this direction in serving as no. 1 you tube channel for simple explanations on Practical AI,ML coding and more people will join with you soon and soon...
Indeed you are an excellent tutor. Your efforts are greatly appreciated .I am fun of you. I AM an AI and machine learning outreach ,you pave me the way .Thanks a lot for you support
Mr. Modi (Mr. Patel) is one side and rest Opposition (Data Science UA-camr) is on the other side. I really envy you (ONIDA TV) and you command that envy with your highest excellence. I am a retired Sr. Citizen and love data science (not because I understand it) but because of the amazing things that Amazon and Tesla and Google are doing.. Please keep going..and may God give you a very long life..
This was my first to machine/deep learning as i had to do an assignment. Still i understood it vey well and now I'm able to do CNN on my own. Thanks to the tutor :)
how come you tube did not recommend me this way before. Your videos are just perfect for people who want to learn Deep Learning and want to overcome the fear of AI
I found something very important. When you reshape your y into 1 dimension, save it in a different variable and use the original one (2d) in the training and test process. Otherwise, the results change a lot
thank you soo much. from the knowledge i gained from this video, i decided to also increase the number of epochs in the first network(ann) from 5 to 10 and that led to a slight increase in the training accuracy(0.49 to 0.54). and for the cnn i intentionally decided first use the SDG optimizer and later the adam which also gave two different but better results than the ann. i also adjusted the epochs in each case. this has given me some more ideas to play around with, with regards to this model. once again thank you for bn such a great teacher
me too i searched for my issue accuracy was 10 % and no increase however i increased hidden layers epochs , but what help me is changing the softmax to sigmoid and the number of hidden units it was 4 on my project here i found it 3000 , it increase my accuracy too , but based on what he choosed 3000 and 1000 hidden units ?
@@ahmedhelal920 More hidden units will recognize more patterns and more features, which will help if your images have many patterns and objects. It is always recommended to use more hidden units on layers and decrease it after every layer to reach a better solution.
Hi, thanks for the clear explanation. I was wondering why you did not use softmax activation function in the last layer instead of sigmoid? As far as I know, softmax is preferred in multiclass problems (like in this case) and sigmoid is used for binary classification problems. Let me know and I appreciate your answer in advance.
yes it might. you can try adding them. sometimes too many layers will overfit a model and while accuracy improves on training set, on test set it might perform poorly. You can use regularization techniques such as adding dropout layer to tackle these issues partially
haven't watch the entire video yet. Is there a way to type in a command which looks for statistical outliers in the data that don't match anything well , so they can be eliminated to improve the model?
the VIdeo is really help full, but you should have also to show where you data set is store, because I am accessing but unable to access my data set from my computer
IT's not the case Dhaval, that ANN is performing badly, if you change the y_train/y_test to categorical and use loss='categorical_crossentropy' it's giving 91% accuracy. I feel CNN will perform certainly better but we may need much higher dataset.
Hello, can you please guide for the K-NN, MLP, CNN, Decision Tree, K-Mean Clustering, regression to solve this CIFAR-10 dataset problem. And compare the accuracies for each of the methodologies used.
how can you get more accuracy? I have messed around with the hyper parameters a lot but I can't seem to find something that gets me a good accuracy (above 80-85)
Sometimes i have thoughts in my mind that is this really happening or is this valuable( i am not judging or not even assuming) as this type of course are paid and with huge amount of money with high demand but how you can give this for freeee ??????? How sir how ??? Hats off👍👍👍👍👍and big thanks 👌👌👌 🙏🙏🙏🙏 I think this learning won't be stopped ever from you.
ha ha... that's a nice way of appreciating my work Ajay. Thank you. Well this course is not free, the fee you need to pay is share this with as many as you can (via linkedin, watsapp, facebook groups, quora etc) :)
Here 9:13 I believe since this is a multiclass classification, we should be using Softmax instead of sigmoid as the activation function in the last layer. Do you think it should be corrected?
Also the way we input the number of neurons in the hidden layer has to be systematically picked. There has to be some organized approach. I know about this klearn library which I found while just looking it up on google. Anyone with more insights please comment. It will be useful! Thanks!
Aashish, for multilabel classification sigmoid is preferred whereas for multiclass classification softmax is a popular choice. So you are right that I should have used softmax here. I will update the notebook when I get a chance but if you have time can you give me a pull request?
@@aashishchaubeyschannel2676 hey Aashish don't worry I just updated the notebook and uploaded it on github. We are all set and thanks for your feedback
I hope you are doing...I had an assignment of image classification and we were suppose to make a confusion matrix I searched on your channel ...and couldn't find any related to confusion matrix. Please make one on that
can i use a similar cnn for object recognition? I want to give multiple labels for each image and in the output i would need the bounding boxes and the corresponding predicted label. How to prepare the dataset accordingly if i were to implement a cnn implemented in the video?Or are there any other deep learning models i could build for this application?
sir I am really appreciated, the way you teach all the concepts related to CNN, and how to build it, sir how can get more accuracy using Keras tuner, please make a video on that.
Sir, i don't know what wrong happen i follow your video's and write same code on my jupyter notebook it is taking too much time on processing i am using dell, i5, 11 gen laptop, still taking too much time for processing Is that cifar10 huge dataset ? What i do, any suggestion ??
Great video thank you for your efforts in creating this , just a small doubt when I replicated the ANN model and ran the code without normalizing the data X_train and test Im getting 100% accuracy in train as well as test where as after normalizing it comes down to 50% and in this video you said then normalization is done to increase the accuracy then how is it happening? (Thank you in for your answer)
Thanks a lot for your great courses, is it possible for you to explain my question? How should we add non-image features to our CNN model (features like cat and dog prices) to our flatten layer? Does the CNN model new added features belong to which input image?
Thank you for the awesome tutorial. I have one question. Is there a way so I could give a path to one folder and then it would classify images which are in it using this model?
Your videos are very good...you explain every line of code...it really helps me a lot to teach ML to my students...your videos are even more useful then other ML videos...👌😊
i basically need to give an ai images and a numerical values, then i want to predict the numerical value from an image, is this kind of model suitable? what do you suggest?
You are doing an amazing work.. I really get intrest in ml after watching your video explanation.. Sir I'm work on project "image classification using deep neural network" The data set is *CIFAR 10*. Paper on which I'm working it already has 80.2% of accuracy . So by using deep neural network algorithms can I make accuracy beyond 80%
I have one doubt.. like here we are working for colored images , we have 3 channels RGB , so do we need filters also different for all the channels or there will be only 1 filter?
Check our Deep Learning Course (in PyTorch) with Latest, Industry Relevant Content: tinyurl.com/4p9vmmds
Check out our premium machine learning course with 2 Industry projects: codebasics.io/courses/machine-learning-for-data-science-beginners-to-advanced
sir plese plese reply i am doing a project on pcb defect detection using cnn model please help me out i am not getting it please help me
From Brazil, you are the best ML teacher!!! Thank you.
Thanks Luciano for your kind words
Excellent tutorials much better than many highly paid course floating online..Thanks a lot sir ..your videos helped me lot ...
From South Korea, Learning Much Faster, Accurate than Univ. Thanks
🤗🤗🙏
We Asians are for us ❤
lol
Your tutorials are truly outstanding, surpassing many paid online courses. I want to express my deep appreciation for the invaluable support they've offered. Your detailed explanations of each code line have been incredibly helpful, particularly when I'm teaching machine learning to my students. Your videos provide a level of comprehension and utility that distinguishes them from other machine learning resources. Your efforts are greatly appreciated... Cheers!!!!!!!!!!!!!!!!💥💫💢
You are so much better than my university tutors :-D Thanks a lot for your help!
I am a young Ai and machine learning engineer from a IIIT and your videos are like food for me if i don't eat then I can't live .Great explanation ...
finally I commented after watching tons of your videos daily . Salute to your spirit sir you will reach 10 M subs soon cause AI and ML is growing exponentially and your videos in this direction in serving as no. 1 you tube channel for simple explanations on Practical AI,ML coding and more people will join with you soon and soon...
Ha ha .. thanks for your kind words of appreciation my friend :)
I started to learn ml after getting inspirations from your videos. Thank you !
Happy to hear that sabrina!
@@codebasics lol lo
Plpp
Pl
@@codebasics pl
the important CNN concept is explained in superb and simple to understand , Thanks a lot
Indeed you are an excellent tutor. Your efforts are greatly appreciated .I am fun of you. I AM an AI and machine learning outreach ,you pave me the way .Thanks a lot for you support
as you teach all concepts even a primary student can understand it easily. Seriously big fan of your teaching style
someone give this man a life elixir, he must give this knowledge for all the future generations
Mr. Modi (Mr. Patel) is one side and rest Opposition (Data Science UA-camr) is on the other side.
I really envy you (ONIDA TV) and you command that envy with your highest excellence.
I am a retired Sr. Citizen and love data science (not because I understand it) but because of the amazing things that Amazon and Tesla and Google are doing..
Please keep going..and may God give you a very long life..
This was my first to machine/deep learning as i had to do an assignment. Still i understood it vey well and now I'm able to do CNN on my own. Thanks to the tutor :)
how to split the image data into training and testing in folders
Excellent tutorials much better than my professor! You are the best! thank you so much! your videos helped me a lot....
how come you tube did not recommend me this way before. Your videos are just perfect for people who want to learn Deep Learning and want to overcome the fear of AI
Exciting Times!! May this series long continue😁
yes it will. My goal is to cove all the topics and make this your one stop place for deep learning
For digits: ann gives 90%, cnn gives 99+% on train dataset and 99% on test data, thanks sir
Thank you sir! Teaching is also a skill and you nailed it!
From Bangladesh...very helpful ❤
sir when i running all this code in google colab my accuracy is 0.1 and not increasing in cnn case also.
I found something very important. When you reshape your y into 1 dimension, save it in a different variable and use the original one (2d) in the training and test process. Otherwise, the results change a lot
Why results change alot?
I love your way of teaching
The ann model refuse to run. It saying keras has no attribute sequential
Such a Good Content.
I am really exciting for upcoming videos.
Glad to hear that
thank you soo much. from the knowledge i gained from this video, i decided to also increase the number of epochs in the first network(ann) from 5 to 10 and that led to a slight increase in the training accuracy(0.49 to 0.54). and for the cnn i intentionally decided first use the SDG optimizer and later the adam which also gave two different but better results than the ann. i also adjusted the epochs in each case. this has given me some more ideas to play around with, with regards to this model. once again thank you for bn such a great teacher
me too i searched for my issue accuracy was 10 % and no increase however i increased hidden layers epochs , but what help me is changing the softmax to sigmoid and the number of hidden units it was 4 on my project here i found it 3000 , it increase my accuracy too , but based on what he choosed 3000 and 1000 hidden units ?
@@ahmedhelal920 More hidden units will recognize more patterns and more features, which will help if your images have many patterns and objects. It is always recommended to use more hidden units on layers and decrease it after every layer to reach a better solution.
You are the best teacher of mine. I'm grateful to you always. Thanks a lot, sir.
Zeenat, thanks for you kind words
No one in universe can teach like this
Thanks zain for your kind words
REALLY A GOOD VIDEO , i finally understood implementing CNN using CIFAR10
You are superb in teaching. Please make video on how to deploy such trained models to production.
Hi, thanks for the clear explanation. I was wondering why you did not use softmax activation function in the last layer instead of sigmoid? As far as I know, softmax is preferred in multiclass problems (like in this case) and sigmoid is used for binary classification problems. Let me know and I appreciate your answer in advance.
Thank you...this course has been inspiring
Amazing tutorial, thanks a lot for sharing! Saludos desde Argentina! 🇦🇷
Very good explanation with a clear easily understandable video. Thank you for your tutorial. Loved it.
thank you from Finland
Your classes are really beginner friendly and I have a doubt will adding more layers improves the accuracy
yes it might. you can try adding them. sometimes too many layers will overfit a model and while accuracy improves on training set, on test set it might perform poorly. You can use regularization techniques such as adding dropout layer to tackle these issues partially
thanks a lot sir for your explanation. i got accuracy of 98.97% using cnn model
Great job
Can you share with your code?
haven't watch the entire video yet. Is there a way to type in a command which looks for statistical outliers in the data that don't match anything well , so they can be eliminated to improve the model?
Very nice explanation on CNN....
how you can simplify such complex topics ? You must be having rich experience in this field...😊
Dear Sir, I have a data-frame with shape: 6500 rows and 146 cols. It is not a 3D data. How can I apply input_shape parameter to use CNN model?
sir how i convert the prediction into csv file with column names (filname and label)
convert to pandas dataframe and just execute - df.to_csv('df.csv')
Thank you sir, excellent explanation
Your approach is very well. You can explain the topics so well and easy to understand the complex topic.
Glad to hear that, I am happy this was helpful to you.
the VIdeo is really help full, but you should have also to show where you data set is store, because I am accessing but unable to access my data set from my computer
Hi Thank you for all your tremendous work you make fall in love with Machine learning. don't you dare to stop;) Thank you so so so much.
Thanks for your kind words khan ☺️ and yes now after reading your comment I am not going to stop 😉
@@codebasics bless you.
IT's not the case Dhaval, that ANN is performing badly, if you change the y_train/y_test to categorical and use loss='categorical_crossentropy' it's giving 91% accuracy. I feel CNN will perform certainly better but we may need much higher dataset.
Thank you
model.evaluate:10000/10000 [==================] - 1s 57us/sample - loss: 0.0275 - accuracy: 0.9910
All the way superb!!!! All videos.
@codebasics why flattening again in model when reshape() is used to do it ??
Hello, can you please guide for the K-NN, MLP, CNN, Decision Tree, K-Mean Clustering, regression to solve this CIFAR-10 dataset problem. And compare the accuracies for each of the methodologies used.
how can you get more accuracy? I have messed around with the hyper parameters a lot but I can't seem to find something that gets me a good accuracy (above 80-85)
Excellent explanation. 👏
We should use softmax for multiclass classification right?. But here we used sigmoid? How is it executing?
very nicely explained brother. Loved the teaching style and followed the explanation
😊😊👍
Could you explain in detail about the reshaping process, on why its necessary ?
Sir I have a problem...when I have to do same code of you in my computer it takes more time in computing .....can you help me please!?
Excellent demo, saved my time.
really good explanations. thanks for your great help
please explain that, why you reshape x_train in exercise, and also change input_shape in conv2D
I’m from Taiwan. It’s really helpful
Glad it was helpful!
I want to use the weights in the hardware upper model in the model. So how do I print out that weight (I'm a beginner)
Sir ,why images are blur can we use our own dataset in same way?
Very lucid explanation
Thank you, It is a great tutorial😍 on CNN
How can I train my own custom data sets? How do I load in my own data when i want to do multiple classification in different folders.
You are the best by far
I am happy this was helpful to you.
Where is the jupyter notebook code link? Plz share
Sometimes i have thoughts in my mind that is this really happening or is this valuable( i am not judging or not even assuming) as this type of course are paid and with huge amount of money with high demand but how you can give this for freeee ???????
How sir how ???
Hats off👍👍👍👍👍and big thanks 👌👌👌
🙏🙏🙏🙏
I think this learning won't be stopped ever from you.
ha ha... that's a nice way of appreciating my work Ajay. Thank you. Well this course is not free, the fee you need to pay is share this with as many as you can (via linkedin, watsapp, facebook groups, quora etc) :)
@@codebasics will do it definitely
✌✌Long live developers👍👍👍
how does the machine decide the filter and the weights in it to detect a feature??
Awesome really like the face to face introduction
Glad you like it
Excellent content! Thank you very much.
Here 9:13 I believe since this is a multiclass classification, we should be using Softmax instead of sigmoid as the activation function in the last layer. Do you think it should be corrected?
Also the way we input the number of neurons in the hidden layer has to be systematically picked. There has to be some organized approach. I know about this klearn library which I found while just looking it up on google. Anyone with more insights please comment. It will be useful! Thanks!
Aashish, for multilabel classification sigmoid is preferred whereas for multiclass classification softmax is a popular choice. So you are right that I should have used softmax here. I will update the notebook when I get a chance but if you have time can you give me a pull request?
@@codebasics sure, let me do that!
@@aashishchaubeyschannel2676 hey Aashish don't worry I just updated the notebook and uploaded it on github. We are all set and thanks for your feedback
Realy sir I like your teaching way
Thanks and welcome
Really nice video...its helped me lot...
I want you to start Audio, Video processing tutorial also because I like it your teaching skills.
Glad it was helpful!
I hope you are doing...I had an assignment of image classification and we were suppose to make a confusion matrix I searched on your channel ...and couldn't find any related to confusion matrix. Please make one on that
can i use a similar cnn for object recognition? I want to give multiple labels for each image and in the output i would need the bounding boxes and the corresponding predicted label. How to prepare the dataset accordingly if i were to implement a cnn implemented in the video?Or are there any other deep learning models i could build for this application?
Tq so munch sir for continuing this series amazing content supreb nice explantion
You're most welcome sathiya
sir I am really appreciated, the way you teach all the concepts related to CNN, and how to build it,
sir how can get more accuracy using Keras tuner, please make a video on that.
Sir, i don't know what wrong happen i follow your video's and write same code on my jupyter notebook it is taking too much time on processing i am using dell, i5, 11 gen laptop, still taking too much time for processing
Is that cifar10 huge dataset ? What i do, any suggestion ??
Great video thank you for your efforts in creating this , just a small doubt when I replicated the ANN model and ran the code without normalizing the data X_train and test Im getting 100% accuracy in train as well as test where as after normalizing it comes down to 50% and in this video you said then normalization is done to increase the accuracy then how is it happening? (Thank you in for your answer)
How Can I build model by using my own images for multiple calssification , thank you
Sir Kernel dying at cnn.fit, i cant proceed , please help, the epoch animation doesnt even begin
Thanks a lot for your great courses, is it possible for you to explain my question? How should we add non-image features to our CNN model (features like cat and dog prices) to our flatten layer? Does the CNN model new added features belong to which input image?
While execution CNN architecture i am getting the kernal appears to have died .it will restart automatically.how can I fix that
Thank you for the awesome tutorial. I have one question. Is there a way so I could give a path to one folder and then it would classify images which are in it using this model?
Yes you can use tensorflow dataset pipeline for that watch TF data pipeline tutorial in this same playlist
@@codebasics Thank You, I'll definitely watch it.
Your videos are very good...you explain every line of code...it really helps me a lot to teach ML to my students...your videos are even more useful then other ML videos...👌😊
Glad you like them!
i basically need to give an ai images and a numerical values, then i want to predict the numerical value from an image, is this kind of model suitable? what do you suggest?
Sir please pass the output of last Conv2d layer to an LSTM layer.
Sir how can I add an LSTM layer at last in the model?
Thank you so much for detailed tutorial. Can you please make a video on Object detection? Specially Faster RCNN and Yolo models.
great job sir.....keep making videos love to watch and learn from your videos
How to choose specific classes in CIFAR-100, if I don't want to use all of the data classes?
how can we access images from sub directories for example there are images(female(23-24), male(23-24))
You are doing an amazing work.. I really get intrest in ml after watching your video explanation..
Sir I'm work on project "image classification using deep neural network" The data set is *CIFAR 10*. Paper on which I'm working it already has 80.2% of accuracy . So by using deep neural network algorithms can I make accuracy beyond 80%
Sir, please tell how to input many images other than cifar from pc in jupyter for performing CNN algorithm.
So are you executing everything in a GPU?
I have one doubt.. like here we are working for colored images , we have 3 channels RGB , so do we need filters also different for all the channels or there will be only 1 filter?
You are really inspirational and have so much to idolize. Thank you!
Glad it was helpful!
sir how to load the dataset if it is not available already in the Keras or TensorFlow library.
Nice tutorial sir. Can you create a chatbot using ANN? I would like to know how you will test that. Thanks!