Hello sir! I am currently in final year of B.E IT engg and doing a deep learning based project. I need advice on your behalf. Please let me know how to contact you. Thanks🙏🏻

This find is a Gem!! Thankyou

thanks a lot

Thank you so much for such a detailed explanation

Thx

Can i use this code for animal recognition

after executing ths: !darknet/darknet detector train Image_Dataset/labelled_data.data darknet/cfg/yolov3_custom.cfg custom_weight/darknet53.conv.74 -dont_show -map i did not get any epoch files to my backup folder please help i have to submit my project in my college.

Sir, My final year project is related to Automated Fruit Ripeness Detection using Deep Learning model. There will e at least four fruits , we have to train model to classify fruit either Underripe, ripe or overripe. Can you please help me. Can I make a GUI we-based in Flask in Google Collab??? or I should make Web Flask app using VS code and then integrate my model at Google Collab? Which will be more convenient for me? One more thing in your video there are two cases(happy or not happy) and you kept it binary. Is there any ternary option available for three classes? underripe, ripe and overipe?

Bro doing this ubundu or windows is poossible to doing wind

The best video ever🙏

Thank you 👍🏻🎉 for easy tutorial of CNn

One of the best video on Nlp🎉 thank you for the tutorial ❤

so helpful.I'm glad Sir

🎯 Key points for quick navigation: 00:14 *Train a neural network to classify mood (happy/not happy) using custom images from Google Photos.* 01:34 *Organize images into training, testing, and validation folders for efficient model training.* 05:31 *Use `ImageDataGenerator` in TensorFlow to preprocess and label images automatically.* 09:00 *Design a convolutional neural network (CNN) for image classification, including convolutional and max pooling layers.* 11:19 *Compile and train the model using binary cross-entropy loss and RMSprop optimizer.* 13:55 *Achieve 100% accuracy on a small dataset; discuss implications and potential improvements.* Made with HARPA AI

Sir, i want to know that which model the CNN model used in this video is inspired from?

i want The song name 11:31

to the point video.👏

You are Amazing!!!! This is the first Relu explanation on KZbin that I've ever found that is actually acceptable for beginner tutoring. You have no idea how big the difference is between your video and what else I've scoured for over the years. Thank you thank you thank you! This video makes every other Relu explanation look like total nonsense. You are the best!

Thanks for the video, i got the concept, but regarding the number of operations in 2:48 are you talking about FLOPs if so, we still need to take the addition operation into account, or are you referring to MACs

Please post the source code of this.

Hey, I like your video a lot. However, at 4:30, how exactly did you call this image from your folder? I can't quite seem to figure it out as you didn't show exactly how you called it. Also, when I type in "img = image.load_img("basedata/train/happy/3.PNG"), it's telling me that the file isn't found and there is no such file, even though there is since I created it. Lastly, when I type in "plt.imshow(img)", it's telling me that the name 'img' is not defined. Please help...I'm following your video and this is throwing me off. Thanks

this is very helpful. I bet if you were picking sad and happy from pictures of friends, the error goes up because too much variation in the photos

Best explanation on the internet.

18:50 There is nothing in train.txt and test.txt how to solve that problem

20.31. Where is the darknet53.convo.74 file

Thnx sir ❤

why 8*8, not 12*12 to find the total number of multiplication ?

Can u please share the link of notebook

clear explanation, thank you so much

Sir can u provide us the code

Pls tell how to create classification report for this? @whenmathsmeetcoding1836

Thank you for your video, great explanation

🥰🥰 bhai maja agya thank you vmro

Thankyou brother Thankyou ❤️ 🙏 💙 🙌

Wooo ... Beautifully explained. Thanks

Please make one video on bert model with such custom dataset sir it will really help me and our subscribers family 🙏🏻

This is a great video there is no explanation of backpropagation in theory video only a feedforward explanation is there

This is a great video. Understood every step of feed-forward network. Where is 2nd part? is it uploaded? Could you please provide a link?

Quality Content ...Keep Going Sir

Thank u. this video has helped me twice.

how to install darknet in local system?

Hi all, Could someone help me how to resolve the below error? line 15: layer_out = net.forward(last_layer) error: error Traceback (most recent call last) Cell In[15], line 1 ----> 1 layer_out = net.forward(last_layer) error: OpenCV(4.9.0) D:\a\opencv-python\opencv-python\opencv\modules\dnn\src\layers\fully_connected_layer.cpp:216: error: (-215:Assertion failed) srcMat.dims == 2 && srcMat.cols == weights.cols && dstMat.rows == srcMat.rows && dstMat.cols == weights.rows && srcMat.type() == weights.type() && weights.type() == dstMat.type() && srcMat.type() == CV_32F && (biasMat.empty() || (biasMat.type() == srcMat.type() && biasMat.isContinuous() && (int)biasMat.total() == dstMat.cols)) in function 'cv::dnn::FullyConnectedLayerImpl::FullyConnected::run'

Everything was fine until you hard coded the thresholding values . This hit and trial is difficult especially with an actual dataset.

anyone following along using the label studio app which is newer version of labelmg should just annotate their dataset and then press exposrt scroll down and then click export in yolo format and then follow along

Tensorflow 3.7 only available

Python genrade error please kindly help me

thanks bhai

Awesome video! Thank you for simplifying things so well.

What if we have a multiple label...what should i give in class_mode ?

Thanks sir it helped a lot