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Applications of AI and Machine Learning

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Using Natural Language Processing
Description

In this lesson, students will learn about tokenizing text to be used in Natural Language Processing models. They will then use that along with embedding layers to create text sentiment models.

Objective

Students will be able to:

  • Explain what tokenization is and why it is important to machine learning
  • Explain how embedding layers are used to create text-based machine learning models
Description

In this lesson, students will learn about recurrent neural networks (RNN) and apply it to create a text-generating model using unsupervised input data.

Objective

Students will be able to:

  • Explain the basics of how an RNN works and why it would be used
  • Create a text-generating model that uses unsupervised data