R squared metric linear regression model supervised learning clustering double descent reinforcement learning train error test error Gauss- Markov theorem confidence intervals test data train data blackbox Python unsupervised learning learning algorithm Occam's razor overfitting residuals underfitting features classification bias- variance tradeoff labels R squared metric linear regression model supervised learning clustering double descent reinforcement learning train error test error Gauss- Markov theorem confidence intervals test data train data blackbox Python unsupervised learning learning algorithm Occam's razor overfitting residuals underfitting features classification bias- variance tradeoff labels
(Print) Use this randomly generated list as your call list when playing the game. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.
O-R squared metric
N-linear regression model
B-supervised learning
B-clustering
I-double descent
I-reinforcement learning
N-train error
I-test error
G-Gauss-Markov theorem
O-confidence intervals
N-test data
G-train data
B-blackbox
B-Python
O-unsupervised learning
G-learning algorithm
I-Occam's razor
I-overfitting
G-residuals
O-underfitting
G-features
N-classification
O-bias-variance tradeoff
B-labels