13 Deep Learning Frameworks for Natural Language Processing in Python

Chainer, developed by the Japanese company Preferred Networks founded in 2014, is a powerful, flexible, and intuitive Python-based framework for neural networks that adopts a "define-by-run" scheme [1]. It stores the history of computation instead of programming logic. The framework released under the MIT License and is already applied for sentiment analysis, machine translation, speech recognition, question answering, and so on using different types of neural networks like convolutional networks, recurrent networks, and sequence to sequence models [2]. Deeplearning4j is a deep learning Java programming library, but it also has a Python API, Keras that will be described below. Distributed CPUs and GPUs, parallel training via iterative reduce, and micro-service architecture adaptation are its main features [3].