Report the output values of the model for the following 4 test data points (use the values at iteration 30, assuming that iteration 0 denotes the beginning) Data point 1 = (-1,-1,-1) Data point 2 = (0.1, 0.2.0.3) Data point 3 = (0.5, 0.5, 0.5) Data point 4 = (1.5, 2, 0.5)

(1) Runnable codes in Python. (task: 12 marks, instructions and comments: 5 marks, in total 17 marks)

(2) A report in PDF format (8 marks) should have the following sections a. A description of how to handle the missing values in your code and report the results. (2.5 Marks) b. A description of the regression technique you used. (3 Marks) c. A description of the results to report. (2.5 Marks)

Lab 05 - Artificial Intelligence 1. What are some of the features included in the housing dataset? 2. In the housing model what is the label or the answer we are trying to predict? 3. In the housing model, how many total data points are there? How many are used to train the ML system? How many are used for testing the efficacy of the system? 4. What does this syntax mean? 5. What kind of weight does the median income feature have in the housing model set and why? 6. What is the one most influencing feature we use in the Python code to predict the median house value in the housing model? 7. What are the high level three steps that you should take when reviewing a machine learning system?

What possible business models (ways of making money) can the company consider?

What are the strengths and limitations of PFN's technologies?