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What is Data Collection for CNN Training about?

Gathering a large amount of balanced training data from diverse examples is important for building an accurate text classifier. The data should then be processed using CNN which involves feature extraction in the convolution layer, data compression in the pooling layer, and vectorization and training in the fully connected layer to produce the final output. Filtering methods can be used to preprocess data by selecting statistically correlated features before machine learning algorithms are applied for class

Author

Akhila R

Language

EN