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TensorFlow

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  Analyzed about 23 hours ago

TensorFlow™ is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy ... [More] computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well. [Less]

3.83M lines of code

798 current contributors

1 day since last commit

23 users on Open Hub

Very High Activity
5.0
 
0 Reviews
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Mostly written in C++
Licenses: apache_2
Tags c++ deep_learning deep_neural_networks flow_graphs GPU gpu_computing machine_learning mobile numerical_computing python

pytorch

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  No analysis available

Tensors and Dynamic neural networks in Python with strong GPU acceleration

0 lines of code

894 current contributors

0 since last commit

5 users on Open Hub

Activity Not Available
0.0
 
0 Reviews
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Mostly written in language not available
Licenses: BSD-3-Clause
Tags deep_learning deep_neural_networks gpu machine_learning machinelearning optimization python

MLPACK C++ machine learning library

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  Analyzed 4 months ago

MLPACK is a fast C++ machine learning library with an emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and maximum ... [More] flexibility for expert users. It contains algorithms such as k-means, Gaussian mixture models, hidden Markov models, density estimation trees, kernel PCA, locality-sensitive hashing, sparse coding, linear regression, least-angle regression, etc. [Less]

276K lines of code

71 current contributors

4 months since last commit

1 users on Open Hub

Activity Not Available
0.0
 
0 Reviews
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Mostly written in C++
Licenses: No declared licenses
Tags algorithms artificial_intelligence classification clustering collaborative_filtering data_mining deep_neural_networks linear_algebra machine_learning optimization pattern_recognition regression

MXNet

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Claimed by Apache Software Foundation Analyzed about 17 hours ago

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Go, and more MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix the flavours of symbolic programming and ... [More] imperative programming together to maximize the efficiency and your productivity. In its core, a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer is build on top, which makes symbolic execution fast and memory efficient. The library is portable and lightweight, and is ready scales to multiple GPUs, and multiple machines. [Less]

424K lines of code

208 current contributors

about 1 year since last commit

1 users on Open Hub

Very Low Activity
0.0
 
0 Reviews
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Mostly written in C++
Licenses: apache_2
Tags bigdata cloud_computing cluster cpu CUDA deep_learning deep_neural_networks distributed efficiency flow_graphs framework gpu 8 more...

h2o-ml

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  Analyzed about 1 hour ago

Fast Scalable Machine Learning API For Smarter Applications (Deep Learning, GBM, GLM...) H2O scales statistics, machine learning, and math over Big Data. H2O uses familiar interfaces like R, Python, Scala, the Flow notebook graphical interface, Excel, & JSON so that Big Data enthusiasts ... [More] & experts can explore, munge, model, and score datasets using a range of algorithms including advanced ones like Deep Learning. H2O is extensible so that developers can add data transformations and model algorithms of their choice and access them through all of those clients. Data collection is easy. Decision making is hard. H2O makes it fast and easy to derive insights from your data through faster and better predictive modeling. H2O allows online scoring and modeling in a single platform. [Less]

613K lines of code

46 current contributors

about 21 hours since last commit

1 users on Open Hub

High Activity
0.0
 
0 Reviews
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Mostly written in Java
Licenses: No declared licenses
Tags ai deep_learning deep_neural_networks

MagNet-DL

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  Analyzed about 15 hours ago

Deep Learning Projects that Build Themselves

2.4K lines of code

0 current contributors

over 5 years since last commit

1 users on Open Hub

Inactive
0.0
 
0 Reviews
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Mostly written in Python
Licenses: No declared licenses
Tags artificial_intelligence convolutional_networks deep_learning deep_neural_networks machine_learning