MOZARK Data Scientist Interview Questions and Answers

Developed a machine learning model to predict customer churn for a telecom company

• Used Python and scikit-learn for data preprocessing and model building

• Performed feature engineering to improve model performance

• Evaluated model using metrics like accuracy, precision, and recall

• Implemented the model in a production environment for real-time predictions

Decision Trees are a popular machine learning algorithm used for classification and regression tasks.

• Decision Trees are a tree-like structure where each internal node represents a feature or attribute, each branch represents a decision rule, and each leaf node represents the outcome.

• They are easy to interpret and visualize, making them popular for exploratory data analysis.

• Decision Trees can handle both numerical and c...read more

LLMs can be finetuned by adjusting hyperparameters, training on specific datasets, and using techniques like transfer learning.

• Adjust hyperparameters such as learning rate, batch size, and number of layers to improve performance.

• Train the LLM on domain-specific datasets to improve its understanding of specialized language.

• Utilize transfer learning by starting with a pre-trained LLM model and fine-tuning it on a smaller...read more