4 Interesting Deep Learning Algorithms 1. Artificial Neural Networks (ANNs) 👉 With 3 Layers - Input layer : No computation is performed, just used for passing information from the outside to the network. - Hidden layer : Deriving complex relationships between input and output. Identifies the pattern in the dataset, learning the data representation and for extracting the features. We cloud use many hidden layers, each layer is responsible for extracting important features. - Output layer: Number of neurons in the output layer is based on the type of problem we want our network to solve (Example: binary classification, number of neurons in the output layer is one). ⏩ Other Concept: - Activation functions ( ex: sigmoid, tanh, ReLU, softmax ): To introduce a non-linear transformation to learn the complex underlying patterns in the data. - Cost function: Use Optimization Algorithms (Gradient descent) to minimize cost so that Network predictions will b...
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