General Terms Flashcards
1
Q
Impution
A
xxx
2
Q
Permutation
A
xxx
3
Q
hyperparameter
A
xxx
4
Q
feature/data scaling
A
xxx
5
Q
scaler
A
xxx
6
Q
multi-class classification
A
xxx
7
Q
binary classification
A
xxx
8
Q
parameter sweep
A
xxx
9
Q
training loss, validation loss, training accuracy, and validation accuracy
A
xxxx
10
Q
clustering
A
xxx
11
Q
centroids
A
xxx
12
Q
overfitting
A
xxx
13
Q
data imbalance
A
xxx
14
Q
feature extraction
feature selection
feature reduction
A
xxx
15
Q
cost factor
A
xxx
16
Q
stopping criteria
A
xxx
17
Q
sampling strategy
A
xxx
18
Q
Model fit
A
xxx
19
Q
model training
A
xxx
20
Q
testing
A
xxx
21
Q
Data visualization
A
xxx
22
Q
evaluation strategy
A
xxx
23
Q
modeling strategy
A
xxxx
24
Q
batch inferencing
A
xxx
25
data movement
xxx
26
dataset
xxx
27
Task Types - Classification
xxx
28
data drift
xxx
29
confusion matrix
xxx
30
model explainer
xxx
31
Azure Machine Learning Hyperdrive
xxx
32
Estimator
xxx
33
workspace
xxx
34
experiment
xxx
35
pipeline
xxx
36
entry script
xxx
37
scoring script
xxx
