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1) The principles of CNNs including convolution, ReLU activation, and max pooling for extracting features from images.
2) How CNN stacks are used along with a fully connected layer to generate predictions from feature maps.
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2. It describes how CNN stacks work with a fully connected layer at the end to calculate probabilities for each label. The feature maps from CNN layers are input to the neural network and a softmax activation assigns decimal probabilities.
3. It discusses techniques for avoiding overfitting like data augmentation, dropout regularization, and transfer learning. Data augmentation artificially increases data variety, dropout removes activations during training,SAS 際際滷s FINALE (2)
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The document summarizes the findings of an analysis conducted to optimize the go-to-market strategy for a new product release in a competitive market. The analysis sought to answer three questions: 1) What product specifications dominate customer sentiment? Screens, cameras, and battery life were found to be the most important specs. 2) Who are the most suitable reviewers to engage for marketing? Several objective reviewers who review multiple brands and models were identified. 3) When is the best time to release the product? May and November were found to have higher customer satisfaction, with tablets more popular in those months and certain companies dominating each release window.