Artifical Intelligence (AI) Flashcards
machines that can perform tasks that require human intelligence
artificial intelligence (AI)
developing algorithms and models that can allow computers to perform tasks without explicit instructions; primary focus is working with and learning from data
machine learning (ML)
a computational model featuring a collection of nodes organized into layers
neural network
occurs when you train your model on input data and output data (called labels); useful for classification tasks
supervised learning
matrix used to evaluate the performance of a supervised learning model
confusion matrix
the four entries in the confusion matrix
true positives (TP); true negatives (TN); false positives (FP); false negatives (FN)
correctly identified something as positive
true positive
correctly identified something as negative
true negative
incorrectly identified something as positive
false positive (type 1 error)
incorrectly identified something as negative
false negative (type 2 error)
we do not provide our model any labels; our model can learn properties about the data on its own; great for associations and clustering
unsupervised learning
one or more agents learn to make decisions as they interact with the environment; they receive rewards and penalties; respond to this feedback; new actions will maximize their rewards over time
reinforcement learning