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