Using Python for machine learning
Python is a popular language in the data scientist community because of its simplicity, cross-platform compatibilities, and rich support for data analysis and data processing through its libraries. One of the key steps in machine learning is preparing data for building the ML models, and Python is a natural winner in doing this. The only challenge in using Python is that it is an interpreted language, so the speed of executing code is slow in comparison to languages such as C. But this is not a major issue as there are libraries available to maximize Python's speed by using multiple cores of central processing units (CPUs) or graphics processing units (GPUs) in parallel.
In the next subsection, we will introduce a few Python libraries for machine learning.
Introducing machine learning libraries in Python
Python comes with several machine learning libraries. We already mentioned supporting libraries such as NumPy, SciPy, and...
