Which dimensionality reduction technique is commonly used to visualize high-dimensional data by projecting it onto a lower-dimensional space while preserving variance?
What evaluation metric measures the proportion of true positives among all actual positives (true positives + false negatives)?
Which type of sampling ensures that each member of the population has an equal chance of being selected for a sample?
What framework is widely used for distributed processing of large datasets across computer clusters, often associated with its MapReduce programming model?
In the context of ethics in AI, what concept refers to a systematic and repeatable error in a computer system's output that creates unfair outcomes for certain groups?
What is the term for the problem in deep neural networks where gradients become extremely small during backpropagation, effectively preventing earlier layers from updating their weights?
Which non-parametric statistical test is used to compare the medians of two independent groups and is often an alternative to the independent samples t-test when data is not normally distributed?
In Reinforcement Learning, what does the 'Q' in Q-learning specifically represent?
What specific type of recurrent neural network (RNN) architecture is designed to overcome the vanishing gradient problem by using 'gates' to control the flow of information?
Which specific data visualization tool is known for its ability to create interactive dashboards and is widely used for business intelligence?