In this modern world, along with artificial intelligence, another term which goes hand in hand is machine learning. Machine learning is implemented for bringing out the power in an exciting way. Most engineers find ML to be complex because of its excessive involvement with computational tasks. Plethora of Python libraries have been created to perform these computational tasks and keep complex lines of code at bay. Here is a list of the most important machine learning libraries every ML enthusiast must know of in order to kick-start their ML journey.
1) TensorFlow
TensorFlow is a popular open source Python Library used for artificial intelligence related errands such as using data flow graphs to build models. This library is a boon for developers who are inclined mainly into working with neural networks of multiple layers. The library TensorFlow is mainly used for classification, understanding, prediction, creation and perception related work.
2) Caffe
Convolution Architecture for Fast Feature Embedding or commonly referred to as Caffe, this library is a popular for deep learning frameworks and is written in C++. Caffe is used by computer science engineers who focus mainly on developing an expressive architecture with extensible coding.
3) Microsoft Cognitive Toolkit (CNTK)
The Microsoft Cognitive Toolkit is an open source toolkit which is used popularly for commercial grade distribute learning. According to this toolkit, neural networks are defined as computational steps via direct graph. CNTK is for making user realise and combine popular model types constitutional neural networks (CNN), DNNs and RNN/LSTMs. Microsoft cognitive toolkit uses stochastic gradient descent learning along with automatic differentiation and penalization for many graphical processing units and severs.
4) Mlpack Library
Mlpack is a crucial library for ML developers. This fast and flexible library is written in C++ language. Mlpack is popular for providing the user with basic command-line programs, Julia Bindings, Python bindings and classes in C++ language. This library is implemented in large scale machine learning solutions. Mlpack is a library which has high emphasis on scalability, efficiency and the ease of use.
5) Shogun
Shogun is a free open source ML library which is also written in C++ language. This library offers several intriguing algorithms and data structures for machine learning based problems. Shogun library is implemented in C++ and effectively provides the user with a unified interface to languages such as Octave, Python, Java, Ruby, C#, Lua and R.
