Tracking datasets with DVC in MLOps - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to initialize a new DVC project in the current directory.

MLOps

dvc [1]

Drag options to blanks, or click blank then click option'

Astart

Bsetup

Ccreate

Dinit

Attempts:

3 left

💡 Hint

Common Mistakes

Using commands like 'start' or 'create' which do not exist in DVC.

The dvc init command initializes DVC in your project folder by creating necessary configuration files.

2fill in blank

medium

Complete the code to add a dataset file named 'data.csv' to DVC tracking.

MLOps

dvc [1] data.csv

Drag options to blanks, or click blank then click option'

Aadd

Btrack

Cpush

Dcommit

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'push' which uploads data but does not add it locally.

The dvc add command tells DVC to track the specified file or directory.

3fill in blank

hard

Fix the error in the command to push tracked data to remote storage.

MLOps

dvc [1]

Drag options to blanks, or click blank then click option'

Asend

Bupload

Cpush

Dsync

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'upload' or 'send' which are not valid DVC commands.

The correct command to upload tracked data files to remote storage is dvc push.

4fill in blank

hard

Fill both blanks to create a DVC pipeline stage that runs 'python train.py' and tracks 'data.csv' as input.

MLOps

dvc run -n train_model -d [1] -o model.pkl [2]

Drag options to blanks, or click blank then click option'

Adata.csv

Bpython train.py

Ctrain.py

Dpython run.py

Attempts:

3 left

💡 Hint

Common Mistakes

Using the script name without 'python' or wrong script names.

The -d flag specifies the dependency file data.csv, and the last argument is the command to run the training script.

5fill in blank

hard

Fill all three blanks to create a DVC stage that takes 'data.csv' as input, runs 'python preprocess.py', and outputs 'clean_data.csv'.

MLOps

dvc run -n preprocess_data -d [1] -o [2] [3]

Drag options to blanks, or click blank then click option'

Adata.csv

Bclean_data.csv

Cpython preprocess.py

Dpreprocess.py

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting to include 'python' before the script name.

The -d flag is for the input file data.csv, -o for the output clean_data.csv, and the command runs the preprocessing script.