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