Speed Mark Logistics Interview Questions and Answers

To transpose a matrix in Python, use numpy.transpose() or the T attribute.

• Use numpy.transpose() function to transpose a matrix.

• Alternatively, use the T attribute of a numpy array.

• Example: np.transpose(matrix) or matrix.T

AU ROC Curve is used to evaluate the performance of classification models by measuring the trade-off between true positive rate and false positive rate.

• AU ROC Curve is commonly used in binary classification problems.

• It helps in comparing different models based on their ability to distinguish between classes.

• The area under the ROC curve (AUROC) value closer to 1 indicates a better model performance.

• For example, in healthcare, AU ROC Curve can be used to evaluate the performanc...read more

Handle missing values by imputation, deletion, or using algorithms that can handle missing data.

• Impute missing values using mean, median, mode, or predictive modeling

• Delete rows or columns with missing values if they are insignificant

• Use algorithms like XGBoost, Random Forest, or LightGBM that can handle missing data

NumPy is a library for numerical computing in Python, while Pandas is a data manipulation and analysis tool.

• NumPy provides support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays.

• Pandas offers data structures like DataFrame for easy data manipulation and analysis, with tools for reading and writing data from various file formats.

• Both libraries are commonly used in data science and machine learning ...read more

Logistic regression is a statistical model used to predict the probability of a binary outcome based on one or more predictor variables.

• Logistic regression is used when the dependent variable is binary (0/1, yes/no, true/false, etc.)

• It estimates the probability that a given observation belongs to a particular category.

• The output of logistic regression is a probability score between 0 and 1.

• It uses the logistic function (sigmoid function) to model the relationship between the ...read more

Python has various visualization libraries like Matplotlib, Seaborn, Plotly, and Bokeh.

• Matplotlib is a widely used library for creating static, interactive, and animated plots.

• Seaborn is built on top of Matplotlib and provides a high-level interface for creating attractive and informative statistical graphics.

• Plotly is great for creating interactive plots and dashboards.

• Bokeh is another interactive visualization library that targets modern web browsers for presentation.