Free DY0-001 sample questions

Correct answers: Docker; Kubernetes

Docker is used to create containers, which package the model, its dependencies, and the API server into a single, isolated, and portable unit. This addresses the isolation and versioning requirement.

Kubernetes is a container orchestration platform that manages containerized applications (like those created with Docker) at scale. It handles auto-scaling, load balancing, and self-healing, which is essential for a high-traffic application.

Correct answer: True

This statement accurately describes the process of transfer learning. A model pre-trained on a large, general dataset (like ImageNet) has already learned useful features. This knowledge is transferred by using its weights as a starting point for training on a new, smaller, and more specific dataset, which is a highly effective technique when data is limited.

Correct answer: Use a managed Apache Spark service to run a large-scale Alternating Least Squares (ALS) collaborative filtering algorithm for daily batch training. For the cold-start problem, supplement with a content-based model. Serve pre-computed recommendations from a low-latency NoSQL database and use a separate real-time model for session-based updates.

This solution is the most comprehensive. It uses a managed Spark service (e.g., AWS EMR, Databricks, GCP Dataproc) to handle the massive scale of batch training, which aligns with the team's need to minimize infrastructure overhead. It correctly uses the ALS algorithm, which is designed for large-scale collaborative filtering. It explicitly addresses the cold-start problem with a hybrid approach (content-based model). Finally, it uses a low-latency NoSQL database (like DynamoDB or Cassandra) for serving, which is a best practice for real-time recommendation systems.

Correct answer: t-Distributed Stochastic Neighbor Embedding (t-SNE)

t-SNE is a non-linear dimensionality reduction technique specifically designed for visualizing high-dimensional data in low-dimensional space (typically 2D or 3D). It excels at revealing the underlying structure of data, such as clusters, by preserving the local similarities between data points. PCA, in contrast, is a linear technique focused on maximizing variance and may not effectively separate clusters that are not linearly separable.

Correct answer: The mean is greater than the median.

A right-skewed (or positively skewed) distribution has a long tail extending to the right. This is caused by a smaller number of high-value outliers pulling the mean to the right. In such a distribution, the typical relationship is Mean > Median > Mode. The median is less affected by outliers than the mean, so it remains closer to the bulk of the data.

Correct answer: Model drift

Model drift, also known as concept drift, occurs when the statistical properties of the target variable, which the model is trying to predict, change over time in unforeseen ways. This causes the model, which was trained on historical data, to become less accurate as time passes. The gradual decrease in performance is a classic symptom of model drift, often caused by changes in fraudulent behavior patterns.

Correct answer: Tokenization, stop word removal, and TF-IDF vectorization

This represents a standard and effective pipeline for text classification. 1) Tokenization breaks the text into individual words (tokens). 2) Stop word removal eliminates common words ('the', 'a', 'is') that add little semantic value. 3) TF-IDF (Term Frequency-Inverse Document Frequency) vectorization converts the cleaned text into numerical vectors that represent the importance of each word in the context of the entire corpus, which is an ideal input for most machine learning classifiers.

Correct answer: True

This is the correct definition of the R-squared (coefficient of determination) value. It is a statistical measure that provides a 'goodness of fit' for the model, indicating how much of the variability in the outcome data can be explained by the model's inputs.

Correct answers: Logistic Regression; Decision Tree

Logistic Regression is a linear model that is highly interpretable. The coefficients of the model directly indicate the influence of each feature on the predicted outcome's log-odds, making it easy for clinicians to understand which factors are most significant.

Decision Trees are inherently interpretable, often called 'white-box' models. The tree structure provides a clear set of if-then rules that can be easily visualized and followed to understand how a specific prediction was made, which is ideal for clinical review.

Correct answer: True

This statement is the correct definition of the Central Limit Theorem (CLT). It is a fundamental concept in statistics that allows for making inferences about a population mean based on a sample mean, even if the population itself is not normally distributed, provided the sample size is large enough (commonly n > 30).