Teach a Machine

Overview

For this applied problem, you will be taking on the role of a cognitive psychology inspired AI-developer. You’re working for a company that is interested in facial and voice recognition, and have been asked to train an AI to classify at least two categories of faces or voices (for example, smiling vs frowning faces, enthusiastic vs tired voices, etc). You must use Google’s Teachable Machine to train your AI while keeping in mind what you’ve learned about neural networks and knowledge categorization. You will submit a copy of your trained AI along with a justification that explains how it relates to neural networks and limitations of categorization.

What do I have to submit?

Submit your individual justification. Don’t forget to submit your creation and comments in the discussion!

Assignment Details

Step 1. Write your justification.

• Your justification must be at least 4 paragraphs long and use the language of cognitive psychology and psychological science. It must include:
• an introductory paragraph that summarizes the context for the problem and the relevant concepts you identified from the module’s readings;
• at least two body paragraphs which define the two concepts you selected from this module alongside how you implemented them in your creation and support from peer-reviewed sources;
• a final paragraph which restates how your creation solves the applied problem and the real-world implications of this module’s concepts
• Use the reference of https://en.wikibooks.org/wiki/Cognitive_Psychology_and_Cognitive_Neuroscience/Imagery#Introduction_&_History 
• use also https://en.wikibooks.org/wiki/Cognitive_Psychology_and_Cognitive_Neuroscience/Knowledge_Representation_and_Hemispheric_Specialisation#Introduction