Research alternative solutions to Chainer on G2, with real user reviews on competing tools. Other important factors to consider when researching alternatives to Chainer include performance and training. The best overall Chainer alternative is Keras. Other similar apps like Chainer are TFLearn, H2O, PyTorch, and Microsoft Cognitive Toolkit (Formerly CNTK). Chainer alternatives can be found in Artificial Neural Network Software but may also be in Machine Learning Software or Data Science and Machine Learning Platforms.
Keras is a neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
TFlearn is a modular and transparent deep learning library built on top of Tensorflow that provide a higher-level API to TensorFlow in order to facilitate and speed-up experimentations, while remaining fully transparent and compatible with it.
H2O is a tool that makes it possible for anyone to easily apply machine learning and predictive analytics to solve today's most challenging business problems, it combine the power of highly advanced algorithms, the freedom of open source, and the capacity of truly scalable in-memory processing for big data on one or many nodes.
Microsoft Cognitive Toolkit is an open-source, commercial-grade toolkit that empowers user to harness the intelligence within massive datasets through deep learning by providing uncompromised scaling, speed and accuracy with commercial-grade quality and compatibility with the programming languages and algorithms already use.
NVIDIA Deep Learning GPU Training System (DIGITS) deep learning for data science and research to quickly design deep neural network (DNN) for image classification and object detection tasks using real-time network behavior visualization.
AIToolbox is a toolbox of AI modules written in Swift: Graphs/Trees, Linear Regression, Support Vector Machines, Neural Networks, PCA, KMeans, Genetic Algorithms, MDP, Mixture of Gaussians, Logistic Regression
DeepPy is a MIT licensed deep learning framework that tries to add a touch of zen to deep learning as it allows for Pythonic programming based on NumPy's ndarray,has a small and easily extensible codebase, runs on CPU or Nvidia GPUs and implements the following network architectures feedforward networks, convnets, siamese networks and autoencoders.
Preconfigured and optimized containers for deep learning environments.
Torch is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first.