Building a machine learning model is just the first step, in many cases, you need to access the built
models
later to speed up your learning process or your data dimensions for each model...
In the following tutorial, I talk about Multiprocessing in Python. By using Multiprocessing, you can
break
the task between processors of the network. Moreover, the accumulated computational time will reduce
Create an account on PyPI, Build a repository on Github (example), Create a setup.py
The reason for selecting this method to talk about is that in machine learning, sometimes we need to
rank our
results and observations to have better insight for making the final decision.
Imagine you trained separate machine learning models or one model over different datasets and have
independent outputs for various datasets. Now, you need to have a final or intermediate report from
the files
before going to the next steps. Therefore, you have to analyze all the results.