Sklearn introduction

Sklearn, sciKit-Learn, is an open source Machine learning toolkit based on the Python language. It uses numpy, SCIpy, Matplotlib, pandas and other Python libraries to implement efficient algorithm applications, covering almost all mainstream machine learning algorithms.

In engineering, in python library to build the basis of machine learning algorithms is very slow, but still recommended based library to build the learning phase using machine learning algorithms, can further algorithm), and error-prone, and often most of the time in the machine learning (70%) was conducted in the data processing, the construction of a qualified data set, With only a small amount of time to build model code and direct calls to the mature algorithm toolkit, we can find a balance between the efficiency and effectiveness of engineering applications, which is exactly what SkLearn brings to our advantage.

Sklearn has a complete and rich official website, which explains in detail the implementation of skLearn algorithm mathematical principle, optimization method and simple application, is a set of very good documents, I believe that in the learning stage carefully read the official website documents will harvest a lot!!

Below I provide the link to the official documentation of Sklearn, as well as the Chinese documentation of a third party since the original is in English.

Chinese document

English document