Image: What is DeepLearning
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:link: deep-learning/nn
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Neural Networks 👨💻
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Neural networks are a class of machine learning models inspired by the structure and function of the human brain. They consist of interconnected nodes (neurons) organized in layers, including an input layer, one or more hidden layers, and an output layer. Each neuron processes input data by applying a weighted sum, followed by an activation function, to produce an output. Neural networks are trained using algorithms like backpropagation, where the model adjusts its internal parameters (weights) based on the errors between predicted and actual outputs.
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:link: deep-learning/cnn/cnn
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CNN Basics💾
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Convolutional Neural Networks are a specialized type of neural network designed for processing structured grid-like data, such as images. They consist of multiple layers, including convolutional layers, pooling layers, and fully connected layers. CNNs use convolutional operations to extract features from input images, preserving the spatial relationships between pixels. Pooling layers reduce the dimensionality of feature maps, making the model more computationally efficient. CNNs have been highly successful in image classification, object detection, and other computer vision tasks.
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:link: deep-learning/rnn
:link-type: doc
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RNN Basics 🚀
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Recurrent Neural Networks are designed to work with sequential data, such as time series or natural language.They contain recurrent connections that allow information to persist over time, enabling the network to capture temporal dependencies.RNNs process input sequences one element at a time while maintaining an internal state (hidden state) that evolves as new inputs are processed.RNNs are widely used in tasks such as machine translation, speech recognition, and sentiment analysis, where understanding context and sequential patterns is crucial.
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<!-- ```{grid-item-card}
:link: deep-learning/rnn
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```{grid-item-card}
:link: deep-learning/rnn
:link-type: doc
:class-header: bg-light
xxx Basics 🚀
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TODO: RNNs are ...
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Start to read {fas}`arrow-right`
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```{grid-item-card}
:link: deep-learning/rnn
:link-type: doc
:class-header: bg-light
xxx Basics 🚀
^^^
TODO: RNNs are ...
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Start to read {fas}`arrow-right`
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