MLOps Zoomcamp 2025

Homework 2: Experiment Tracking Statistics

Distribution of scores and reported study time for this homework.

Submissions

404

Median total score

6

Average total score

6

Score distribution

All values are points.

Questions score

Min
1
Median
6.0
Max
6
Q1
5.0
Avg
5.4
Q3
6.0

Learning in public score

Min
-
Median
0.0
Max
7
Q1
0.0
Avg
0.6
Q3
0.0

Total score

Min
1
Median
6.0
Max
14
Q1
5.0
Avg
6.1
Q3
6.0

Time distribution

All values are hours reported by students.

Lectures

Min
0.0
Median
4.0
Max
48.0
Q1
3.0
Avg
5.0
Q3
6.0

Homework

Min
0.0
Median
3.0
Max
23.0
Q1
2.0
Avg
3.7
Q3
4.0

Question breakdown

Correctness and answer distribution per question.

1. Install MLflow

404 / 406 correct (99.5%)

Answer Count
2.22.0 243
mlflow, version 2.22.0 58
version 2.22.0 17
pip install mlflow 12
MLflow version: 2.22.0 3
2.18.0 3
'2.22.0' 3
2.22 3
2.12.2 3
2.13.0 2
yes 2
2.20.4 2
2.17.2 2
mlflow, version 2.12.1 2
mlflow==2.22.0 2
1.27.0 2
2.21.3 2
mlflow --version mlflow, version 2.22.0 2
mlflow 2.22.0; Python 3.13.3 1
My version is 2.22.0 1
1 1
2.21.2 1
v2.22.0 1
2.20.1 1
2.22.0 (initially v1.27.0, then downgraded pyarrow for the latest version) 1
1. mlflow, version 2.22.0 1
mlflow, version 2.11.1 1
ml flow, version 2.22.0 1
mlflow, version 2.3.2 1
mlflow, version 2.20.0 1
1.30.0 1
'2.21.3' 1
Mlflow version-2.22.0 1
MLflow version: 2.22.0 1
mlflow version 2.22.0 1
2.15.1 1
2.12.1 1
❯ mlflow --version mlflow, version 2.22.0 1
2.14.3 1
2.21.1 1
ok 1
2.22.2 1
version 2.18.0 1
mlflow, version 2.2.2 1
version 3.0.0rc2 1
mlflow, version 3.0.0rc3 1
2.9.0 1
Yes 1
2.20 1
mlflow, version 2.18.0 1
version 2.17.2 1
Version: 2.22.0 1
mlflow, version 1.30.0 1
mlflow version = 2.22.0 1
2.19.0 1
mlflow, version 2.13.0 1
installed 1

2. Download and preprocess the data

393 / 406 correct (96.8%)

1 1 1 (0.2%)
2 3 7 (1.7%)
3 4 395 (97.3%)
4 7 0 (0.0%)

3. Train a model with autolog

369 / 406 correct (90.9%)

1 2 371 (91.4%)
2 4 20 (4.9%)
3 8 4 (1.0%)
4 10 3 (0.7%)

4. Launch the tracking server locally

361 / 406 correct (88.9%)

1 default-artifact-root 362 (89.2%)
2 serve-artifacts 2 (0.5%)
3 artifacts-only 5 (1.2%)
4 artifacts-destination 29 (7.1%)

5. Tune model hyperparameters

336 / 406 correct (82.8%)

1 4.817 38 (9.4%)
2 5.335 338 (83.3%)
3 5.818 10 (2.5%)
4 6.336 10 (2.5%)

6. Promote the best model to the model registry

329 / 406 correct (81.0%)

1 5.060 41 (10.1%)
2 5.567 332 (81.8%)
3 6.061 15 (3.7%)
4 6.568 5 (1.2%)

Calculated: 31 May 2025, 12:38