AI and Machine Learning
artificial intelligence - correct answerArtificial intelligence is the study of agents that
perceive the world around them, form plans, and make decisions to achieve their goals.
Machine Learning - correct answerMachine learning is a subfield of artificial intelligence.
Its goal is to enable computers to learn on their own. A machine's learning algorithm
enables it to identify patterns in observed data, build models that explain the world, and
predict things without having explicit pre-programmed rules and models.
artificial narrow intelligence (ANI) - correct answerAI which can effectively perform a
narrowly defined task.
Supervised Learning - correct answerAgent observes input-output pairs & learns to map
input to output
Regression - correct answerPredict a continuous numerical value. How much will that
house sell for?
Classifications - correct answerassign a label. Is this a picture of a cat or a dog?
gradient descent - correct answerA technique to minimize loss by computing the
gradients of loss with respect to the model's parameters, conditioned on training data.
Informally, gradient descent iteratively adjusts parameters, gradually finding the best
combination of weights and bias to minimize loss.
Overfitting - correct answerThe process of fitting a model too closely to the training data
for the model to be effective on other data.
Bias - correct answerthe amount of error introduced by approximating real-world
phenomena with a simplified model; goal is to minimize bias, high bias = underfit
Variance - correct answerhow much your model's test error changes based on variation
in the training data. It reflects the model's sensitivity to the idiosyncrasies of the data set
it was trained on; goal is to minimize variance, high variance = overfit
Logistic Regression - correct answera method of classification: the model outputs the
probability of a categorical target variable Y belonging to a certain class.
Support vector machines (SVMs) - correct answerpredictive model approach for
classifying things based on geometry; They attempt to find a plane that separates the
two classes cleanly. When this isn't possible, we either soften the definition of
"separate," or we throw the data into higher dimensions so that we can cleanly separate
the data.
artificial intelligence - correct answerArtificial intelligence is the study of agents that
perceive the world around them, form plans, and make decisions to achieve their goals.
Machine Learning - correct answerMachine learning is a subfield of artificial intelligence.
Its goal is to enable computers to learn on their own. A machine's learning algorithm
enables it to identify patterns in observed data, build models that explain the world, and
predict things without having explicit pre-programmed rules and models.
artificial narrow intelligence (ANI) - correct answerAI which can effectively perform a
narrowly defined task.
Supervised Learning - correct answerAgent observes input-output pairs & learns to map
input to output
Regression - correct answerPredict a continuous numerical value. How much will that
house sell for?
Classifications - correct answerassign a label. Is this a picture of a cat or a dog?
gradient descent - correct answerA technique to minimize loss by computing the
gradients of loss with respect to the model's parameters, conditioned on training data.
Informally, gradient descent iteratively adjusts parameters, gradually finding the best
combination of weights and bias to minimize loss.
Overfitting - correct answerThe process of fitting a model too closely to the training data
for the model to be effective on other data.
Bias - correct answerthe amount of error introduced by approximating real-world
phenomena with a simplified model; goal is to minimize bias, high bias = underfit
Variance - correct answerhow much your model's test error changes based on variation
in the training data. It reflects the model's sensitivity to the idiosyncrasies of the data set
it was trained on; goal is to minimize variance, high variance = overfit
Logistic Regression - correct answera method of classification: the model outputs the
probability of a categorical target variable Y belonging to a certain class.
Support vector machines (SVMs) - correct answerpredictive model approach for
classifying things based on geometry; They attempt to find a plane that separates the
two classes cleanly. When this isn't possible, we either soften the definition of
"separate," or we throw the data into higher dimensions so that we can cleanly separate
the data.
