What is the term for the phenomenon where a machine learning model exhibits unfair or discriminatory behavior due to biased training data or algorithmic design?
What type of neural network is particularly well-suited for processing sequential data like natural language or time series?
Which open-source machine learning library, developed by Google, is widely used for building and training deep neural networks?
What is the process of converting categorical data into a numerical format that machine learning algorithms can understand, without implying any ordinal relationship?
What evaluation metric is used in binary classification to calculate the ratio of correctly predicted positive observations to the total actual positive observations?
In a Decision Tree algorithm, what criterion is often used at each split point to measure the impurity of a node, aiming to maximize homogeneity in resulting child nodes?
In the context of deep learning, what is the primary purpose of a Generative Adversarial Network (GAN)?
Which optimization algorithm, often used in deep learning, adapts the learning rate for each parameter individually based on the past gradients?
What technique is used to explain the predictions of any classifier by approximating the complex model locally with an interpretable one, such as a linear model?
What is the technique in deep learning that involves freezing the weights of initial layers of a pre-trained model and only training the later layers on a new, related dataset?