In a skewed distribution, which measure of central tendency is most resistant to the effects of outliers?

  • Mean
  • Median
  • Mode
  • Geometric Mean
The median is the most resistant measure of central tendency in a skewed distribution. It is less affected by extreme values or outliers since it represents the middle value when the data is arranged in order. The mean, mode, and geometric mean can be heavily influenced by outliers, causing them to be less representative of the data's central location.

What is a common technique to prevent overfitting in linear regression models?

  • Increasing the model complexity
  • Reducing the number of features
  • Regularization
  • Using a smaller training dataset
Regularization is a common technique used to prevent overfitting in linear regression models. It adds a penalty term to the linear regression's cost function to discourage overly complex models. Regularization techniques include L1 (Lasso) and L2 (Ridge) regularization.

In which type of data do you often encounter a mix of structured tables and unstructured text?

  • Structured Data
  • Semi-Structured Data
  • Unstructured Data
  • Multivariate Data
Semi-structured data often contains a mix of structured tables and unstructured text. It's a flexible data format that can combine organized data elements with more free-form content, making it suitable for a wide range of data types and use cases, such as web data and NoSQL databases.

In transfer learning, a model trained on a large dataset is used as a starting point, and the knowledge gained is transferred to a new, _______ task.

  • Completely unrelated
  • Identical
  • Similar
  • Smaller-scale
In transfer learning, a model trained on a large dataset is used as a starting point, and the knowledge gained is transferred to a new, similar task. This leverages the pre-trained model's knowledge to improve performance on the new task, particularly when the tasks are related.

In Data Science, when dealing with large datasets that do not fit into memory, the Python library _______ can be a useful tool for efficient computations.

  • NumPy
  • Pandas
  • Dask
  • SciPy
When working with large datasets that do not fit into memory, the Python library "Dask" is a useful tool for efficient computations. Dask provides parallel and distributed computing capabilities, enabling data scientists to handle larger-than-memory datasets using familiar Python tools.

Which layer type in a neural network is primarily responsible for feature extraction and spatial hierarchy?

  • Input Layer
  • Convolutional Layer
  • Fully Connected Layer
  • Recurrent Layer
Convolutional Layers in neural networks are responsible for feature extraction and learning spatial hierarchies, making them crucial in tasks such as image recognition. They apply filters to the input data, capturing different features.

In time-series data, creating lag features involves using previous time steps as new _______.

  • Predictors
  • Observations
  • Predictions
  • Variables
In time-series analysis, creating lag features means using previous time steps (observations) as new data points. This allows you to incorporate historical information into your model, which can be valuable for forecasting future values in time series data.

Which CNN architecture is known for its residual connections and improved training performance?

  • LeNet
  • VGGNet
  • AlexNet
  • ResNet
Residual Networks (ResNets) are known for their residual connections, which allow for easier training of very deep networks. ResNets have become a standard in deep learning due to their ability to mitigate the vanishing gradient problem, enabling the training of much deeper architectures.

Which activation function can alleviate the vanishing gradient problem to some extent?

  • Sigmoid
  • ReLU (Rectified Linear Unit)
  • Tanh (Hyperbolic Tangent)
  • Leaky ReLU
The ReLU activation function is known for mitigating the vanishing gradient problem, which is a common issue in deep learning. ReLU allows gradients to flow more freely during backpropagation, making it easier to train deep neural networks.

In Tableau, you can connect to various data sources and create a unified view known as a _______.

  • Dashboard
  • Workbook
  • Storyboard
  • Data source
In Tableau, a "Workbook" is where you can connect to various data sources, design visualizations, and create a unified view of your data. It serves as a container for creating and organizing your data visualizations and analyses.