Building the Neural Network

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Keras is a high-level neural network API in Python that simplifies constructing and training neural networks. It is used for tasks involving image and video data, text and audio data, and structured o…

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TensorFlow is an open-source, end-to-end platform for Machine Learning, primarily developed by the Google Brain Team. It is used to build, train, and deploy machine learning models.

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The name comes from its core mechanism: tensors, which are multi-dimensional arrays of data, flow through a graph of operations.

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The five steps are: 1) Prepare Data, 2) Define Model, 3) Compile, 4) Fit or Train, and 5) Evaluate.

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Data is loaded and reshaped or normalized so that the network can read it properly. For image data, pixel values are often scaled from 0 to 1 for better training stability.

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The Sequential model is the easiest way to define a model architecture. It represents a linear stack of layers, where one layer follows another in order.

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A Dense layer is a fully connected layer in which every neuron is connected to every neuron in the previous layer. It performs the heavy lifting of learning patterns.

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A Flatten layer converts a 2D image into a 1D vector. For example, a 28x28 image becomes a line of 784 numbers, because neural networks generally need 1D vectors as input.