Review and comparative analysis of machine learning libraries for machine learning

Abstract

The article is an overview. We carry out the comparison of actual machine learning libraries that can be used the neural networks development. The first part of the article gives a brief description of TensorFlow, PyTorch, Theano, Keras, SciKit Learn libraries, SciPy library stack. An overview of the scope of these libraries and the main technical characteristics, such as performance, supported programming languages, the current state of development is given. In the second part of the article, a comparison of five libraries is carried out on the example of a multilayer perceptron, which is applied to the problem of handwritten digits recognizing. This problem is well known and well suited for testing different types of neural networks. The study time is compared depending on the number of epochs and the accuracy of the classifier. The results of the comparison are presented in the form of graphs of training time and accuracy depending on the number of epochs and in tabular form.

Construction of Intelligent Recognition and Learning Education Platform of National Music Genre Under Deep Learning

“…MATLAB (Matrix &Laboratory) programming software 2016A ( Gevorkyan et al, 2019 ) is used to extract the characteristics of the original music signal. Based on the Python language, the DBN constructed by the Theano library ( Budhi et al, 2021 ) is used, and Spyder ( Baydogan and Aatas, 2021 ) is used as the programming environment.…”

Performance analysis of machine learning libraries

“…Wydajność była mierzona na podstawie czasu treningu sieci neuronowej oraz dokładności rozpoznawania danych pobranych z bazy MNIST. Czas uczenia biblioteki TensorFlow był bardzo podobny do narzędzi Scikitlearn oraz Keras i wynosił od 1 do 3 sekund, co zdecydowanie pokonywało bibliotekę PyTorch, osiągającą czas treningu na poziomie 25 sekund [3].…”

Comparative analysis of machine learning methods by the example of the problem of determining muon decay

“…The library is based on the following principles: simplicity usage, modularity, and extensibility. Our choice of this libraries about is justified in the article [1].…”

“…In the article [1], the authors compared various libraries for building neural networks [8], [12], [24]- [26]. The result of the speed and the accuracy tests show that Keras library provides the most optimal solution.…”

“…In this paper, the authors try to study if deep learning is really superior to all other machine learning methods. Previously, the authors conducted a comparative analysis of the most popular software products for working with neural networks networks [1], and also tried to generalize the methodology for working with machine learning models [2].…”