Sometimes boredom can be a good thing in terms of creativity

I have been studying data science for two and a half years now, and my studies have taken me to becoming knowledgeable of the following subject:-

1. The programming language Python,
2. The numerical library numpy,
3. The data processing library pandas
4. Python’s inbuilt mathematics library math,
5. Python’s inbuilt library for strings, re,
6. The statistical library statsmodels,
7. The machine learning library statsmodels,
8. The graphical library matplotlib, and
9. The graphical library seaborn.

Of course I have been exposed to other libraries in my studies, but the nine mentioned above tend to be the ones that I have tended to veer toward.

It just so happens that sklearn, Python’s machine learning library, is considered to be a toy library that does not have the capacity to handle large datasets. For the training of large datasets, neural networks are for the time being the solution to this conundrum.

For two and a half years, however, I focused my energy on learning how to use sklearn in my machine learning ventures. This was primarily because the documentation for the library is…