Machine learning with Python! Preparation

At the beginning

Last time was only able to maintain the Python environment, so This time, we will go further and prepare for machine learning with Python!

... or rather, it will be a reference bookmark memo. Don't even get to the entrance ... Machine learning

Those who do not know how to write Python in the first place

The following sites may be useful

-Learning site from introduction to application of Python

However, as a caveat, Python is not compatible in writing between 2 and 3 series. Since the printf is written differently, it may not work quite well depending on the site you refer to.

-Changes from Python 2 to Python 3.0

Packages required for machine learning with Python

The following packages seem to be often used in machine learning

NumPy A library that performs processing such as matrix calculation, various mathematical functions, linear algebra, and Fourier transform.
SciPy The core package of scientific computing routines
scikit-learn python machine learning(Machine Learning;Machine learning)Module
matplotlib Python graphing library
pandas Data frame(Tabular data structure convenient for data analysis)Library to create and operate

Please refer to Last time for how to install.

The following may be useful for learning how to use

-Data science with Python

Other

While investigating, when writing Python, the IDE's "Jupyter Notebook" Since it was introduced several times, I will post a link that was easy to understand.

-Powerful notepad for modern engineers Jupyter notebook recommendation -How to build a technical notebook environment using Jupyter Notebook -How to start the Jupyter Notebook server

That's it.

If you have any questions, please comment. mm

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