Question 1: 

Techniques for Predictive Modeling

1. What is the so-called “black-box” syndrome?

2. What is the meaning of “maximum margin hyperplanes”? Why are they important in SVM?

3. Why is it important to be able to explain an ANN’s model structure?

Note: Your initial post will be your answer to the Question and is to be 300 – 400 words with at least two references. Initial post will be graded on length, content, grammar and use of references. References should always be below each question as they are a different topic and not related in any way.

Question 2:

Reflecting on your program of study so far, how does this class prepare you for the world of data visualizations and more specifically, for the presentation of any future presentations? If so, please provide an example of how you would use any of the visualization techniques to present a project for another course. Do you see the techniques you reviewed as an advantage? Or, as a disavantage?

Discussion Length (word count): At least 250 words

References: At least two peer-reviewed, scholarly journal references.

Reference: Kirk, A. (2016). Data Visualisation: A Handbook for Data Driven Design. Thousand Oaks, CA: Sage Publications, Ltd.

Note: At least 250 words (not including direct quotes). References should always be below each question as they are different topic and not related in any way