I love your videos. You show me the path when i was in confusion about start off learning deep learning. Keep going , sir. Great job!!!!!

This channel is massively underrated! Great work 🔥

Your series are very helpful. Great videos to learn

Thanks a lot for your video sir, it's very insightful. I just would like to make sure how many images are in your training datat&test data? Because I m little confused about number 800, during the training, does that mean that your whole dataset has 800 images?

Very good videos. Thank you!

Hey nice tutorial, thanks. I have a question: suppose I want to output a 2D vector in the geometrical sense (x, y). I've divided the output into three parts: axis, sign, and absolute value. These are the conditions: if one axis value is > 0, then the other axis is assumed to be zero. For example, (0, 1) is a valid vector, (3, 0) is a valid vector, but (3, 4) is not a valid vector. Absolute values are bounded between 0 and 7, for example, (0, 7) is a valid vector, but (-1, 0) does not exist in this case. So, my question is this: should I train the network SEPARATELY for each case, meaning, the first nn will do binary classification of the axis, the second nn will do binary classification of the sign and the third nn will do multiclass classification of the values, with one hot encoded data? Thanks again

Really Appreciate and like your videos. Thank You.

Hi, thanks for the tutorial. If possible, could you talk about the implementation of vision transformer(ViT) using keras?

nice video man, very helpful!

Great job sir

Great content. I have one doubt - your validation_generator only apply rescale of 1/255, meaning it will not increase the data size (unlike train_generator where random transformation is applied). Base on this, 1) does the generator repeats the data in an infinite loop until stopped by epoch? 2) if the answer to (1) is no, can I feed a validation_dataset (instead of a generator) into the model.fit() method (b.t.w the TensorFlow docs claims that "model.fit_generator is deprecated and Please use Model.fit, which supports generators")

Spyser seems to work well with ML , any better IDE?

8:30 no issue. Its part of learning and teaching... ❤

can you provide me with the dataset please

i have an errror, it is in line 39, how to resolve it [WinError 3] The system cannot find the path specified: '/images/cell_images/test/Parasitized/'

great lectures

Can I get the dataset?

Sir on line 39 Syntaxerror :cannot assign to operator Aa rha h mainy apny dataset k two folders bnai hn image_directory = 'C:/Users/OWNER/Desktop/single-grn-dataset/' SIZE = 224 Dataset = [ ] Label = [ ] Infected-Grains-Images = os.listdir(image_directory +'C:/Users/OWNER/Desktop/single-grn-dataset/Infected-Grains/ ') SyntaxError: cannot assign to operator Sir I am new plz guide me

sir..great video ..tq so much...how to create this binary classification if my data quiet small ? just 200 dataset?

permission to learn sir