The Python machine learning tool you have to look at

IEEE Spectrum Leaderboard First, Skill up first development tool, stack Overflow the most interesting choice of programmers in the annual survey, stack Overflow the most visited programming language of the June ... Yes, these prestigious points point to a programming language,--python.

Python is widely used in scientific computing: computer vision, artificial intelligence, mathematics, astronomy, and so on. It also applies to machine learning and is expected. This will enumerate and describe Python's most useful machine learning tools and libraries.

In addition, although some modules can be used for a variety of machine learning tasks, only the main focus in the Machine learning Library is listed here. For example, although Scipy1 contains some clustering algorithms, its main focus is not machine learning but a comprehensive set of scientific computing tools. So we ruled out the scipy. (Although we also use it)

? Theano

Theano is the most mature deep learning library. It provides a good data structure (tensor, tensor) to represent the layers of a neural network, which is efficient for linear algebra and similar to numpy arrays.

Decaf

Decaf is a recent deep learning library published by UC Berkeley, tested in the Imagenet Classification challenge, and its neural network implementation is very advanced (state of art).

Nolearn

If you want to use the excellent Scikit-learn Library API in deep learning, encapsulating the decaf Nolearn will make it easier for you to use it. It is the packaging for decaf, compatible with Scikit-learn (mostly), making decaf even more magical. (Thousand front python)

Overfeat

Overfeat is the winner of the recent Cat vs. dog (Kaggle Challenge) 4, which is written in C + + and contains a Python wrapper (as well as MATLAB and LUA). The GPU is used through the torch library, so it's fast. Also won the imagenet classification of detection and localization challenges.

Neurolab

The Neurolab is another API-friendly (similar to MATLABAPI) neural network library. Unlike other libraries, it contains different variants of the recursive neural network (recurrent neural network,rnn) implementations. If you want to use RNN, this library is one of the best choices for the same API.

The Python machine learning tool you have to look at is these, find out if you need it!

The Python machine learning tool you have to look at