Evaluating Current and Future AI Technologies and Frameworks

Artificial Intelligence    |    Intermediate
  • 13 videos | 39m 37s
  • Includes Assessment
  • Earns a Badge
Rating 4.6 of 8 users Rating 4.6 of 8 users (8)
Solid knowledge of the AI technology landscape is fundamental in choosing the right tools to use as an AI Architect. In this course, you'll explore the current and future AI technology landscape, comparing the advantages and disadvantages of common AI platforms and frameworks. You'll move on to examine AI libraries and pre-trained models, distinguishing their advantages and disadvantages. You'll then classify AI datasets and see a list of dataset topics. Finally, You'll learn how to make informed decisions about which AI technology is best suited to your projects.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Compare and contrast ai platforms, frameworks, libraries, pre-trained models, and datasets
    Recognize the key features and advantages/disadvantages of common ai platforms
    Identify the tensorflow framework and distinguish its advantages/disadvantages
    Identify the keras framework and distinguish its advantages/disadvantages
    Identify the pytorch framework and distinguish its advantages/disadvantages
    Identify the mxnet framework and distinguish its advantages/disadvantages
  • Identify the cntk framework and distinguish its advantages/disadvantages
    Identify the cortex framework and explore its key features
    Examine ai libraries and identify their advantages/disadvantages
    Recognize pre-trained models and distinguish their advantages/disadvantages
    Classify ai datasets and recognize a list of dataset topics
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 51s
  • 5m 9s
    Find out how to compare and contrast AI platforms, frameworks, libraries, pre-trained models, and datasets. FREE ACCESS
  • Locked
    3.  AI Platforms: H2O, IBM Watson, Amazon Lex, and MS CS
    6m 51s
    Upon completion of this video, you will be able to recognize the key features and advantages and disadvantages of common AI platforms. FREE ACCESS
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    4.  TensorFlow Framework
    3m 26s
    In this video, you will learn how to identify the TensorFlow framework and distinguish its advantages and disadvantages. FREE ACCESS
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    5.  Keras Framework
    2m 35s
    In this video, find out how to identify the Keras framework and distinguish its advantages and disadvantages. FREE ACCESS
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    6.  PyTorch Framework
    2m 32s
    In this video, you will learn how to identify the PyTorch framework and distinguish its advantages and disadvantages. FREE ACCESS
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    7.  MXNet Framework
    2m 27s
    During this video, you will learn how to identify the MXNet framework and distinguish its advantages and disadvantages. FREE ACCESS
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    8.  CNTK Framework
    2m 16s
    Learn how to identify the CNTK framework and distinguish its advantages and disadvantages. FREE ACCESS
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    9.  Cortex Framework
    2m 36s
    In this video, you will identify the Cortex framework and explore its key features. FREE ACCESS
  • Locked
    10.  AI Libraries
    1m 53s
    In this video, you will examine AI libraries and identify their advantages and disadvantages. FREE ACCESS
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    11.  Pre-trained Models
    4m 12s
    After completing this video, you will be able to recognize pre-trained models and distinguish their advantages and disadvantages. FREE ACCESS
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    12.  AI Datasets
    1m 34s
    In this video, you will learn how to classify AI datasets and recognize a list of dataset topics. FREE ACCESS
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    13.  Course Summary
    2m 16s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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