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The neural network architecture in the image has
4 hidden layers , 5 inputs and 5 outputs
6 hidden layers, 1 input layer and 1 output layer
4 hidden layers , 5 input layers and 5 output layers
6 hidden layers 5 inputs and 2 output layers
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1 The Underpinnings
2 Gradient Descent greedy algorithm
3 cost function graph Minima
4 True about Decision trees
5 Support Vector Machines Classification or Regression
6 Support Vector Machines Supervised Unsupervised
7 Support Vector Machines Margin classifier
8 Linearly Separable
9 Two points to classify
10 Outliers
11 classification models minimum error
12 classification models best model to choose
13 Neurons maximum number of outputs
14 More Layers neurons more accuracy
15 one forward pass and backward pass
16 Examples of deep learning
17 Neural Network
18 Hidden layer
19 regression or classification
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