features labels classification clustering bias- variance tradeoff Python confidence intervals overfitting blackbox residuals supervised learning reinforcement learning linear regression model learning algorithm Occam's razor double descent underfitting train data unsupervised learning R squared metric test data test error Gauss- Markov theorem train error features labels classification clustering bias- variance tradeoff Python confidence intervals overfitting blackbox residuals supervised learning reinforcement learning linear regression model learning algorithm Occam's razor double descent underfitting train data unsupervised learning R squared metric test data test error Gauss- Markov theorem train error
(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.
G-features
B-labels
N-classification
B-clustering
O-bias-variance tradeoff
B-Python
O-confidence intervals
I-overfitting
B-blackbox
G-residuals
B-supervised learning
I-reinforcement learning
N-linear regression model
G-learning algorithm
I-Occam's razor
I-double descent
O-underfitting
G-train data
O-unsupervised learning
O-R squared metric
N-test data
I-test error
G-Gauss-Markov theorem
N-train error