Using Neural Networks for Image and Voice Data Analysis

Neural networks can be configured in various ways depending on the type of data and objectives. This course will help you understand how to properly choose a neural network architecture for image or audio data.
Deep learning, as opposed to machine learning, allows a more robust way to deal with image and audio data for various data science problems such as classification and clustering. This is largely due to the power of neural networks and their ability to learn the proper features to represent images and audio data without having to handpick such features as one would in traditional machine learning. However, understanding the correct architecture of the neural network is integral to get the best possible result.
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