Data Science Methodology

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1.
Data-Science
2.
Problem-Scoping
3.
Design-Thinking
4.
Analytic-Approach
5.
Descriptive-Analytics
6.
Diagnostic-Analytics
7.
Predictive-Analytics
8.
Prescriptive-Analytics
9.
Data-Requirements
10.
Data-Collection
11.
Data-Understanding
12.
Data-Preparation
13.
Feature-Engineering
14.
Model-Building
15.
Algorithm-Selection
16.
Training-Data
17.
Testing-Data
18.
Cross-Validation
19.
Over-Fitting
20.
Under-Fitting
21.
Performance-Metrics
22.
Precision-Score
23.
Recall-Score
24.
F1-Score
25.
Mean-Squared-Error
26.
Root-Mean-Squared-Error
27.
Coefficient-of-Determination
28.
Model-Deployment
29.
Feedback-Loop
30.
Time-Series