Introduction to sklearn
Sklearn, fully known as scikit learn, is an open source machine learning toolkit based on Python language. It realizes efficient algorithm application through Python libraries such as numpy, SciPy, Matplotlib and pandas, and covers almost all mainstream machine learning algorithms.
In the project, it is very inefficient to use Python’s basic library to build machine learning algorithm (but it is recommended to use the basic library to build machine learning algorithm in the learning stage, which can further deepen the algorithm), and it is also prone to errors. In machine learning, most of the time (70%) is to process data and build qualified data sets, Only a small part of the time is spent building model code and directly calling the mature algorithm toolkit, which can find a balance between the efficiency and effect of engineering application, which is the advantage sklearn brings us.
Sklearn has a complete and rich official website, which explains in detail the algorithm, mathematical principle, optimization method and simple application of sklearn. It is a set of very excellent documents. I believe you will gain a lot by carefully consulting the official website documents in the learning stage!!
Below, I provide a link to the official documents of sklearn. Since the original text is in English, I also provide a third-party Chinese document.