Well the good thing is that one doesn't need to possess a PhD-level understanding of the theoretical aspects of machine learning in order to practice. Hence, the best way to get started using Python for machine learning is to complete a small project. |
It would be highly recommended for one to try this project - "Project Hello World of Machine Learning in Python"
This is a good project because it is so well understood.
*Attributes are numeric so you have to work out how to load and handle data. *It is a classification problem, allowing you to practice with perhaps an easier type of supervised learning algorithm. *It is a multi-class classification problem (multi-nominal) that may require some specialized handling. *It only has 4 attributes and 150 rows, meaning it is small and easily fits into memory (and a screen or A4 page). *All of the numeric attributes are in the same units and the same scale, not requiring any special scaling or transforms to get started.
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