NIce ! i have a question about 19:00 you said if bias is 0 the neuron is dead I think it's wrong cuz we have Wxalfa as linear function and activation function as non-linear function then why did you say that can you explain it it me? thanks alot
Hi.. i have a doubt in the last code that you have shown.. If you are using sigmoid at the last dense layer and since sigmoid give us only one probability value , i think u need to give only 1 output layer . but 2 were given.. am I correct?
Hi Sreeni, great videos. Without you I could have never started image analysis! Question: I followed your video on using watershed segmentation and regionprops and it works great to find grains in an image and their area! My problem is that with in each of these grains there are different metals (cobalt, copper, ect) that map the location of. Like if you had a bunch of cells and nuclei and wanted to know both the cell size and the nucli size for each. I cannot figure out how to find the sub-regions' area and assign them to the same label as the larger region. Would I need deep learning for this?
Great, great work! I'm doing my BSc project now and the materials you prepared are saving my life! You're a great teacher.
One of the best tutorials on machine learning, Thank you for your time and effort.
You're very welcome!
Two words: Thank you
Such many explanations and clarifications!
Thank you so much! Very clear and good information for a beginner!!!!
I really enjoyed very much during your presentation. Thank you very much for your fluent and simple explanation.
saved a lot of my time for my assignment , thank you so much sir
amazing video - thank you for creating this wonderful content
great material for deep learning !! to the point, great work. thanks
NIce ! i have a question about 19:00 you said if bias is 0 the neuron is dead I think it's wrong cuz we have Wxalfa as linear function and activation function as non-linear function then why did you say that can you explain it it me? thanks alot
Thanks... Great contents and well explained.
Glad you liked it!
very neat and clear explanation
thanks a lot, keep the great work!!
Very underrated channel!
Thank you. Please do help spread the word.
Sreenivas sir deserve million likes...
you are the best sir thank you so much
Most welcome
very well explained! thanks.
Hi.. i have a doubt in the last code that you have shown.. If you are using sigmoid at the last dense layer and since sigmoid give us only one probability value , i think u need to give only 1 output layer . but 2 were given.. am I correct?
Hi Sreeni, great videos. Without you I could have never started image analysis! Question: I followed your video on using watershed segmentation and regionprops and it works great to find grains in an image and their area! My problem is that with in each of these grains there are different metals (cobalt, copper, ect) that map the location of. Like if you had a bunch of cells and nuclei and wanted to know both the cell size and the nucli size for each. I cannot figure out how to find the sub-regions' area and assign them to the same label as the larger region. Would I need deep learning for this?
Sooo helpful again
your great thank you
Happy to help!
Soo helpful thanks a lot from France!
Thank you boss
How to drop irrelevant features to save model with relevant features? With irrelevant features, model takes huge amount of memory...
Great!
very interesting thank you very much.But i need nlp algorithm like RNN,LSTM and attention mechanism if you have time please help me.
@sreeni thanks so much for the video clip. May I ask if you have the github link? Thanks
github.com/bnsreenu/python_for_microscopists
i love you