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Gorgonia is a library that helps facilitate machine learning in Go. Write and evaluate mathematical equations involving multidimensional arrays easily. If this sounds like Theano or TensorFlow, it's because the idea is quite similar. Specifically, the library is pretty low-level, like Theano, but has higher goals like Tensorflow.The main reason to use Gorgonia is developer comfort. If you're using a Go stack extensively, now you have access to the ability to create production-ready machine learning systems in an environment that you are already familiar and comfortable with.

machine-learning artificial-intelligence neural-network computation-graph differentiation gradient-descent gorgonia deep-learning deeplearning deep-neural-networks automatic-differentiation symbolic-differentiation go-libraryApache MXNet (incubating) is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scaling effectively to multiple GPUs and multiple machines.MXNet is also more than a deep learning project. It is also a collection of blue prints and guidelines for building deep learning systems, and interesting insights of DL systems for hackers.

deep-learning deep-neural-networks mxnet distributed-systems machine-learning artificial-intelligenceCaffe2 is a lightweight, modular, and scalable deep learning framework. Building on the original Caffe, Caffe2 is designed with expression, speed, and modularity in mind.

deep-learning machine-learning ai artificial-intelligence caffe2 deep-neural-networks mlGorgonia is a library that helps facilitate machine learning in Go. Write and evaluate mathematical equations involving multidimensional arrays easily. If this sounds like Theano or TensorFlow, it's because the idea is quite similar. Specifically, the library is pretty low-level, like Theano, but has higher goals like Tensorflow. The main reason to use Gorgonia is developer comfort. If you're using a Go stack extensively, now you have access to the ability to create production-ready machine learning systems in an environment that you are already familiar and comfortable with.

machine-learning artificial-intelligence neural-network computation-graph differentiation gradient-descent gorgonia deep-learning deeplearning deep-neural-networks automatic-differentiation symbolic-differentiationCaffe2 is a lightweight, modular, and scalable deep learning framework. Building on the original Caffe, Caffe2 is designed with expression, speed, and modularity in mind.

deep-learning machine-learning ai artificial-intelligence caffe2 deep-neural-networks mlCountdown timers to keep track of a bunch of CV/NLP/ML/AI conference deadlines.

deep-learning deep-neural-networks machine-learning computer-vision artificial-intelligence natural-language-processing roboticsTrending deep learning Github repositories can be found here. Hint: This will be updated regularly.

deep-learning deep-neural-networks deep-reinforcement-learning convolutional-neural-networks recurrent-neural-networks stargazers-count artificial-neural-networks artificial-intelligence machine-learning top-repositoriesSummaries of papers on deep learning.

deep-learning deep-neural-networks computer-vision machine-learning artificial-intelligenceFortran 95 Based Nueral Networks and Stochastic Gradient Descent. Examples located in /tests directory. To run examples run make from that directory.

nueral-networks deep-learning deep-neural-networks machine-learning artificial-intelligenceCaffe2 for iOS. A simple integration into existing projects. and run pod install.

caffe2 deep-learning deep-neural-networks ai artificial-intelligence cocoapods-specsRepositories with 50000 stars or more are excluded. Top deep learning Github repositories can be found here.

deep-learning deep-neural-networks trending-repositories convolutional-neural-networks recurrent-neural-networks deep-reinforcement-learning stargazers-count artificial-neural-networks artificial-intelligence machine-learningUnofficial,PyTorch version of Deep Image Analogy.https://arxiv.org/abs/1705.01088. This project focuses on documentation of the project , and simplifying the structure. A blog post on it is coming soon. This project uses Adam as optimizer instead of LBFGS. LBFGS was giving really poor results.

deep-learning deep-neural-networks pytorch pytorch-tutorial neural-network machine-learning artificial-intelligence
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