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Session #1 Homework

Solution:

Set up the environment

You need to install Python, NumPy, Pandas, Matplotlib and Seaborn. For that, you can the instructions from 06-environment.md.

Question 1

What's the version of NumPy that you installed?

You can get the version information using the __version__ field:

np.__version__

Getting the data

For this homework, we'll use the Car price dataset. Download it from here.

You can do it with wget:

wget https://raw.githubusercontent.com/alexeygrigorev/mlbookcamp-code/master/chapter-02-car-price/data.csv

Or just open it with your browser and click "Save as...".

Now read it with Pandas.

Question 2

How many records are in the dataset?

Here you need to specify the number of rows.

  • 16
  • 6572
  • 11914
  • 18990

Question 3

Who are the most frequent car manufacturers (top-3) according to the dataset?

  • Chevrolet, Volkswagen, Toyota
  • Chevrolet, Ford, Toyota
  • Ford, Volkswagen, Toyota
  • Chevrolet, Ford, Volkswagen

Note: You should rely on "Make" column in this question.

Question 4

What's the number of unique Audi car models in the dataset?

  • 3
  • 16
  • 26
  • 34

Question 5

How many columns in the dataset have missing values?

  • 5
  • 6
  • 7
  • 8

Question 6

  1. Find the median value of "Engine Cylinders" column in the dataset.
  2. Next, calculate the most frequent value of the same "Engine Cylinders".
  3. Use the fillna method to fill the missing values in "Engine Cylinders" with the most frequent value from the previous step.
  4. Now, calculate the median value of "Engine Cylinders" once again.

Has it changed?

Hint: refer to existing mode and median functions to complete the task.

  • Yes
  • No

Question 7

  1. Select all the "Lotus" cars from the dataset.
  2. Select only columns "Engine HP", "Engine Cylinders".
  3. Now drop all duplicated rows using drop_duplicates method (you should get a dataframe with 9 rows).
  4. Get the underlying NumPy array. Let's call it X.
  5. Compute matrix-matrix multiplication between the transpose of X and X. To get the transpose, use X.T. Let's call the result XTX.
  6. Compute the inverse of XTX.
  7. Create an array y with values [1100, 800, 750, 850, 1300, 1000, 1000, 1300, 800].
  8. Multiply the inverse of XTX with the transpose of X, and then multiply the result by y. Call the result w.
  9. What's the value of the first element of w?

Note: You just implemented linear regression. We'll talk about it in the next lesson.

  • -0.0723
  • 4.5949
  • 31.6537
  • 63.5643

Submit the results

  • Submit your results here: https://forms.gle/vLp3mvtnrjJxCZx66
  • You can submit your solution multiple times. In this case, only the last submission will be used
  • If your answer doesn't match options exactly, select the closest one

Deadline

The deadline for submitting is 12 September 2022 (Monday), 23:00 CEST (Berlin time).

After that, the form will be closed.