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Basic Building Blocks: From Shallow to Deep Learning

  • KC Santosh,
  • Rodrigue Rizk,
  • Siddhi K. Bajracharya

摘要

In this chapter, we will discuss the basic building blocks for shallow learning and deep learning. We will go through the traditional machine learning models like regression, classification, clustering, and dimensionality reduction. Afterward, we will also look at deep learning and discuss important architectures such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and transformers.