MLOps Zoomcamp 2024

Homework 2: Experiment Tracking Statistics

Distribution of scores and reported study time for this homework.

Submissions

589

Median total score

6

Average total score

6

Score distribution

All values are points.

Questions score

Min
-
Median
6.0
Max
6
Q1
5.0
Avg
5.5
Q3
6.0

Learning in public score

Min
-
Median
0.0
Max
7
Q1
0.0
Avg
0.5
Q3
0.0

Total score

Min
-
Median
6.0
Max
14
Q1
5.0
Avg
6.0
Q3
6.0

Time distribution

All values are hours reported by students.

Lectures

Min
0.0
Median
4.0
Max
72.0
Q1
3.0
Avg
5.3
Q3
6.0

Homework

Min
0.0
Median
3.0
Max
72.0
Q1
2.0
Avg
4.4
Q3
4.0

Question breakdown

Correctness and answer distribution per question.

1. Install MLflow

585 / 589 correct (99.3%)

Answer Count
2.13.0 291
mlflow, version 2.13.0 111
2.12.2 38
version 2.13.0 26
2.13.1 17
mlflow, version 2.12.2 13
pip install mlflow 12
2.11.3 5
version 2.12.2 5
2.13 5
!pip install mlflow 4
mlflow, version 2.13.1 4
2.3.1 3
mlflow, version 2.12.1 3
'2.13.0' 3
Done 2
2.11.1 2
mlflow, version 2.3.1 2
1.30.1 1
2.1.3 1
mlflow, version 1.30.0 1
MLflow version: 2.13.0 1
mlflow version 2.11.3 1
version 2.13 1
2.12.1 1
mlflow-2.13.1 1
version is 2.13.0 1
2.9.2 1
2.4.1 1
Python 3.9.19 1
MLflow Version: 2.13.0 1
2.13. 1 1
v2.13.0 1
pip install mlflow // mlflow, version 2.13.0 1
'2.13.1' 1
yes 1
MLflow version 2.13.0 1
Yes 1
mlflow, version 1.30.1 1
V=2.13.0 1
version 2.13.1 1
mlflow version 2.13.0 1
```conda create -n exp-tracking``` ```pip install mlflow``` 1
conda installed: 2.12.2 (didn't work); pip installed 2.13.0 1
--version mlflow, version 2.13.0 1
2.8.1 1
Version 2.13.1 1
version 2.11.3 1
Mlflow, version 2.13.1 1
2.5.0 1
mlflow, version 2.3.2 1

2. Download and preprocess the data

570 / 589 correct (96.8%)

1 1 1 (0.2%)
2 3 12 (2.0%)
3 4 574 (97.5%)
4 7 1 (0.2%)

3. Train a model with autolog

541 / 589 correct (91.9%)

1 2 545 (92.5%)
2 4 17 (2.9%)
3 8 6 (1.0%)
4 10 12 (2.0%)

4. Launch the tracking server locally

490 / 589 correct (83.2%)

1 default-artifact-root 492 (83.5%)
2 serve-artifacts 9 (1.5%)
3 artifacts-only 10 (1.7%)
4 artifacts-destination 65 (11.0%)

5. Tune model hyperparameters

538 / 589 correct (91.3%)

1 4.817 14 (2.4%)
2 5.335 540 (91.7%)
3 5.818 13 (2.2%)
4 6.336 10 (1.7%)

6. Promote the best model to the model registry

501 / 589 correct (85.1%)

1 5.060 36 (6.1%)
2 5.567 503 (85.4%)
3 6.061 22 (3.7%)
4 6.568 9 (1.5%)

Calculated: 13 October 2024, 05:00