Neural Networks Explained With Easy Examples!
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YouTubeEdna's Tech Desk
Neural Networks Explained With Easy Examples!
In this video, we break down the concept of neural networks, comparing them to the human brain and showing how they recognize patterns in images and speech. Whether you're diving into deep learning or exploring machine learning fundamentals, this explanation is designed for beginners to grasp complex ideas easily. Join us on this journey to ...
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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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