2018 Most popular Python machine learning Library Introduction

python is an object-oriented, interpretive computer programming language with a rich and powerful library, coupled with its simplicity, ease of learning, speed, open source free, portability, extensibility, and object-oriented features,python Become the most popular programming language of the 2017!

   AI is one of the hottest topics, and machine learning technology is an essential skill for artificial intelligence, The Python programming language contains the most useful machine learning tools and libraries, and the following are the top ten machine learning libraries that Python development engineers must know!

I. Scikit-learn

Ii. Statsmodels

Iii. PyMC

  PYMC is a tool for "Bayesian curve", which contains Bayesian models, statistical distributions and model convergence diagnostic tools, Some hierarchical models are also included.

Iv. Gensim

v. Orange

VI, PyMVPA

Vii. Theano

Viii. PyLearn

IX, Hebel

ten, Neurolab

  neurolab is an API-friendly neural network library that contains different variants of the recursive neural network implementation, If you use RNN, this library is one of the best choices in a homogeneous API.

python Development Engineer must know ten machine learning Library, in addition, there are overfeat, Nolearn and decaf, such as machine learning Library, this will not be introduced, interested in in-depth study!

2018 Most popular Python machine learning Library Introduction