Describe how the training, validation, and testing processes should be organized and available data should be used within a model. What are the impact of overlapping training, validation, and testing data sets. Summarize mitigation strategies and describe the preconditions to their application. Discuss the criteria that you will use to answer the three questions.

Performance analysis a) What is the confusion matrix? b) Why accuracy is not enough to evaluate the performance of an Al model tested on imbalanced dataset and what are the alternative metrics we need to use to study the real performance of the model?

What exactly does it imply when James MacGregor Burns refers to something as a "system model"? What do you think are the most significant factors to take into account while constructing a baseline model?

Next, your task involves analyzing data collected from various sources, interpreting the findings, and presenting them effectively. Based on the concepts and techniques discussed in Module 9:   Describe the process you would follow to analyze both qualitative and quantitative data collected from your research. Include specific methods (e.g., content analysis, thematic analysis for qualitative data, and statistical analysis for quantitative data) and explain why these methods are suitable for your project. Propose strategies for effectively presenting your findings. Consider different presentation methods (e.g., structured notations, storytelling, graphical representations) and justify which method(s) would be most effective for your audience and study goals. Note: Your response should demonstrate a comprehensive understanding of the principles and practices of data analysis, interpretation, and presentation in the context of human-computer interaction.