Evaluating Current and Future AI Technologies and Frameworks

Evaluating Current and Future AI Technologies and Frameworks

• 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

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.