Hi Lawrence, thank you so much for the easy to understand and to the points videos. I have completed a model and am finding a way to deploy it to a webpage. Do you know any good tutorials or books that teach how to deploy models? Appreciate your help!
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“…and the concept remains the same for all networks”. That is a very didactic and useful idea!
That's the goal!
Really nicely explained for layman, I feel like I understand more
Hi Laurence, thanks for the video, it is very interesting. But how do you fed 784 squares to the 20 neirons?
The 'Flatten' layer in Keras handles that for you
@@laurencemoroney655 Thanks for answer
It's the layer of the matrix and which get flatteren in 28 * 28 * 1
Thanks a lot for this!
Hi Lawrence, thank you so much for the easy to understand and to the points videos. I have completed a model and am finding a way to deploy it to a webpage. Do you know any good tutorials or books that teach how to deploy models? Appreciate your help!
Try my book "AI and Machine Learning for On-Device Development" :)
I think this may help ~ ua-cam.com/play/PLtqF5YXg7GLmCvTswG32NqQypOuYkPRUE.html
Have u uploaded it on webpage. If yes how?
May i know the name of the network which you showed as an example? For retinopathy? Is that inception model?
Yes, Inception V1 with 22 layers, but not sure why there is "26 layers" in the caption.
Why are there 20 neurons on the input and not 784?
How do you input 784 data points in 20 neurons
Gracias por tus consejos no se mucho pero aprendo de ustedes 🙏
de nada!
at 6:59 , doesn't this network (GoogleNet) have 22 layers? the caption says 26. am I missing something?
What’s the difference between sparse categorical accuracy and accuracy?
This link is useful: www.tensorflow.org/api_docs/python/tf/keras/metrics/SparseCategoricalAccuracy
Nice one!
TKS my friend
Intresting 🤔
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