ML development tools
We can develop ML models in many languages, ranging from Python, R, C++, Java, and Julia to scientific tools such as proprietary MATLAB and open source Octave. Python is by far the most widely used language in academia, the scientific community, and industry. This makes it a near de facto standard for mainstream ML development. We will be using Python throughout this book.
Python’s simplicity and readability contribute to its popularity, but what sets it apart is the rich ecosystem of scientific and data analysis libraries. NumPy for numeric computing, pandas for data analysis, and Matplotlib for charting are three libraries that are widely used in ML work.
These are available as standard Python packages. The default packager in Python is pip, and you can find and install packages from package repositories, such as the Python Package Index (PyPI). In some operating systems and environments, you may find pip as pip3.
Packages sometimes have other...
