Artificial neural networks (ANN) - explained super simple

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1. What is a neural network?
2. How to train the network with simple example data (1:10)
3. ANN vs Logistic regression (06:42)
4. How to evaluate the network (07:14)
5. How to use the network for prediction (09:23)
6. How to estimate the weights (10:25)
7. Understanding the hidden layers (16:30)
8. ANN vs regression (20:56)
9. How to set up and train an ANN in R (23:08)
  1. TileStats
  2. deep learning
  3. machine learning
  4. AI
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Комментарии
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You are Brilliant. i could not understand the whole concept until you explained in this video.

gaborolah
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Omg, I have tried to understand ANN without success until now. Thank you!

tedransom
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Thank you, looking forward to your next video about ANN

yolavictoria
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best explanation so far! thank you. i have tried it in R using the neuralnet function with your dataset. even though i get the same coefficients with the log regression the weights and bias using the ANN are not the same. they are much lower. any idea why? =/

Salvador_Dali
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why using 2 output nodes? isn't P(healthy) equal to 1-P(cancer)?

a.moa
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for the first calculation, why u get -0.251?, i get -0.26

ahmadmatjek