Deep Learning Packages: Keras - a Neural Network Framework

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Lesson Objectives
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Expertise Level


Keras is a deep learning package suitable for beginners. Although it is applied in multiple standard deep learning use cases, it is also used by commercial-grade products. To facilitate this, Keras provides additional, flexible options on top of the well-known Sequential API, which allow you to customize and create various neural networks. To utilize this, however, requires a more in-depth knowledge of the Keras framework.

In this course, you'll develop the core skills needed to work with the Keras framework. You'll explore the advantages and disadvantages of using Keras over other frameworks, and examine how Keras can be used with TensorFlow.

You'll move on to recognize how Keras is used for machine learning and deep learning. Finally, you'll implement two deep learning projects using the Keras framework.

Expected Duration (hours)

Lesson Objectives

Deep Learning Packages: Keras - a Neural Network Framework

  • discover the key concepts covered in this course
  • describe the Keras framework and define the main concepts needed to work with Keras
  • specify how Keras facilitates cognitive computing
  • specify how Keras facilitates deep learning
  • outline the relationship between TensorFlow and Keras and identify how Keras models can be optimized with TensorFlow
  • recognize the benefits of using Keras
  • describe how Keras can be used with languages such as C/C++ and Java
  • compare Keras with other frameworks and define its advantages and disadvantages
  • describe how to create machine learning models using Keras
  • describe how to create deep learning models using Keras
  • illustrate how to use Keras in combination with cloud services
  • find key documents and resources for in-depth information about the Keras framework
  • work with Keras to implement sentiment analysis of Twitter posts related to a US presidential debate
  • work with Keras to implement a plant disease classifier
  • summarize the key concepts covered in this course
  • Course Number:

    Expertise Level