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Chainer is an open source deep learning framework written purely in Python on top of NumPy and CuPy Python libraries. The development is led by Japanese venture company Preferred Networks in partnership with IBM, Intel, Microsoft, and Nvidia.
Linux, macOS, Windows: Python: Python: Only on Linux No Yes No Yes Yes Keras: François Chollet 2015 MIT license: Yes Linux, macOS, Windows: Python: Python, R: Only if using Theano as backend Can use Theano, Tensorflow or PlaidML as backends Yes No Yes Yes [20] Yes Yes No [21] Yes [22] Yes MATLAB + Deep Learning Toolbox (formally Neural Network ...
Keras is an open-source library that provides a Python interface for artificial neural networks. Keras was first independent software, then integrated into the TensorFlow library, and later supporting more. "Keras 3 is a full rewrite of Keras [and can be used] as a low-level cross-framework language to develop custom components such as layers ...
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
TensorFlow.nn is a module for executing primitive neural network operations on models. [40] Some of these operations include variations of convolutions (1/2/3D, Atrous, depthwise), activation functions ( Softmax , RELU , GELU, Sigmoid , etc.) and their variations, and other operations ( max-pooling , bias-add, etc.).
A large collection of Question to SPARQL specially design for Open Domain Neural Question Answering over DBpedia Knowledgebase. This dataset contains a large collection of Open Neural SPARQL Templates and instances for training Neural SPARQL Machines; it was pre-processed by semi-automatic annotation tools as well as by three SPARQL experts ...
NNI (Neural Network Intelligence) is a free and open-source AutoML toolkit developed by Microsoft. [3] [4] It is used to automate feature engineering, model compression, neural architecture search, and hyper-parameter tuning. [5] [6] The source code is licensed under MIT License and available on GitHub. [7]
Apache MXNet is an open-source deep learning software framework that trains and deploys deep neural networks. It aims to be scalable, allows fast model training, and supports a flexible programming model and multiple programming languages (including C++, Python, Java, Julia, MATLAB, JavaScript, Go, R, Scala, Perl, and Wolfram Language).