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predictions\n\n✅ Analyze housing price predictions that come from a single layer neural network\n\n✅ Use TensorFlow to build a single layer neural network for fitting linear models\n\n✅ Use callback functions for tracking model loss and accuracy during training\n\n✅ Make predictions on how the layer size affects network predictions and training speed\n\n✅ Implement pixel value normalization to speed up network training\n\n✅ Build a multilayer neural network for classifying the Fashion MNIST image dataset\n\n✅ Use callback functions to interrupt training after meeting a threshold accuracy\n\n✅ Test the effect of adding convolution and MaxPooling to the neural network for classifying Fashion MNIST images \n\n✅ Explain and visualize how convolution and MaxPooling aid in image classification tasks\n\n✅ Reflect on the possible shortcomings of your binary classification model implementation\n\n✅ Execute image preprocessing with the Keras ImageDataGenerator functionality\n\n✅ Carry out real 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