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Data Science and Machine Learning Examples for Data Science Linux
Shell Python C
branch: master


Machine Learning Examples for BigDataR Linux

What is an Example?

An Example is a transfer of knowledge that is compeling and easily understood.

How do you do that?

An example must be in the form:
1. Objective.
2. Solution.
3. Value.

Without these three characteristics, understanding a new concept is difficult.

All README files to an example must contain the following


Define what the example is trying to solve and why it is important.


Define how it aims to solve the objective.
Consider inputs, parameters, outputs Why do we need them?
What do they do?
How do they change the output?


What is the outcome and why do we need it.
Why is the solution valueable?
How do I interpret it?
What can I do with it?

END All README files to an example must contain the following


Don't take all of the questions above in the literal sense and simply answer them.
The abstract thought here is these three items (Objective, Solution, Value) formulate a foundation for why we do something.
Understanding why we do something is half the battle when learning anything new.
If we can answer the foundational questions, we can build holistic examples.

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