Machine Learning-Refined Foundations, Algorithms, and Applications Questions and Answers

Machine Learning-Refined Foundations, Algorithms, and
Applications Questions and Answers, A+ GURANTEED

1
Q
What is Machine Learning?


A
The study of algorithms that can learn from data and can make predictions on new data.

2
Q
What are the primary differences between traditional programming versus machine learning
programming?


A
** Traditional Programming **
Can be seen as having one stage
Data -> Program -> Output (Output being the focus)

** Machine Learning **
Can be seen as having two stages
1. Training
Data -> Algorithm -> Output (Algorithm being the focus)

2. Deployment
Data -> Algorithm -> Output (Output being the focus)

3
Q
What is an example of a timeline of machine learning?


A

, Data Collection -> Preprocessing -> Exploratory Data Analysis -> Model Building -> Splitting the
Data -> Training and Validation -> Testing the model -> Deploying the model

4
Q
What is CRISP-DM?


A
CRISP-DM is an acronym for Cross-industry standard process for data mining

It is a commonly used methodology for data mining

It divides data mining into six phases starting from business understanding

5
Q
What are the six stages of CRISP-DM?


A
They are iterative processes (That are also non-linear), but the general stage structure looks like this

Business Understanding Data Understanding -> Data Preparation Modelling -> Evaluation ->
Deployment

6
Q
What is supervised machine learning?


A
Supervised machine learning is when data includes labels

7
Q
What is the goal of supervised machine learning?


A