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