ML Basics With Python | Dataford Interview Questions

Tell me about your understanding of machine learning basics and how you would use Python for it.

Use the tables below to support your answer with a SQL query that identifies the most recent training-ready dataset version for each model project and summarizes its label balance.

Output

One row per model project.
Columns: project_name, dataset_version, feature_count, positive_label_rate, is_training_ready.
Include only projects whose latest dataset version is marked training-ready.
Sort by project_name ascending, then dataset_version descending.

Schema

model_projects

Column	Type	Description
project_idPK	INT	Unique identifier for the ML project
project_name	VARCHAR(255)	Human-readable project name
owner_team	VARCHAR(255)	Team responsible for the project

datasets

Column	Type	Description
dataset_idPK	INT	Unique identifier for the dataset record
project_id	INT	References the ML project
dataset_version	INT	Version number of the dataset
feature_count	INT	Number of input features available
positive_label_rate	DECIMAL(5,4)	Share of positive labels in the dataset
is_training_ready	BOOLEAN	Whether the dataset can be used for training

Your question is ML Basics With Python. Start with the requirements and the two tables in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Problem