Deep Neural Network from Scratch in Python – Fully Connected Feedforward Tutorial
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Deep Neural Network from Scratch in Python – Fully Connected Feedforward Tutorial
Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands-on understanding of deep learning. #DeepLearning #PythonProgramming #NeuralNetworks
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A neural network learns by continuously adjusting its parameters - the weights and biases - to improve its prediction accuracy. These parameters are tweaked upward or downward based on how far the model’s predictions deviate from the actual results. The difference between the predicted output and the true value is measured using a loss function, which quantifies the error. To minimize this error, the model uses backpropagation, an algorithm that calculates the gradients (partial derivatives of t
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