Deep Learning / open source platform

Hint: Click ↑ Pushed to see the most recently updated apps and libraries or click Growing to repos being actively starred .
0
h2o-3 🌿
4706 (+2) ⭐

Open Source Fast Scalable Machine Learning Platform For Smarter Applications: Deep Learning, Gradient Boosting & XGBoost, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

0
FfDL 🌿
594 (+0) ⭐

Fabric for Deep Learning (FfDL, pronounced fiddle) is a Deep Learning Platform offering TensorFlow, Caffe, PyTorch etc. as a Service on Kubernetes

0
atlas 🌿
125 (+2) ⭐

An Open Source, Self-Hosted Platform For Applied Deep Learning Development

0 comments    
0
PyTorch 🌿
15 (+0) ⭐

An open source deep learning platform that provides a seamless path from research prototyping to production deployment

0 comments    
0
neuralet 🌿
28 (+1) ⭐

Neuralet is an open-source platform for edge deep learning models on edge TPU, Jetson Nano, and more.

0 comments    
0
9 (+0) ⭐

Neuralet edge deep learning models library. Neuralet is an open-source platform for edge deep learning models on GPU, TPU, and more.

0 comments    
0
32 (+0) ⭐

An open source implementation of the deep learning platform for undersampled MRI reconstruction described by Hyun et. al. (https://arxiv.org/pdf/1709.02576.pdf)

0
customerml πŸ‚
44 (+0) ⭐

CustomerML is an open source customer science platform leveraging the power of Predictiveworks and fully integrated with Elasticsearch and Shopify. CustomerML starts with proven RFM analysis and combines the results with machine learning thereby providing a deep customer understanding.

0 comments    
0
DeepCamera 🌿
499 (+0) ⭐

Protect your privacy, open source AI-powered video surveillance on Android, featuring face recognition, human shape recognition(ReID), etc. The world's first AutoML Deep Learning edge AI platform. No programming exp needed to train a new model for your privacy.

0
2 (+0) ⭐

The Deep Learning Seminar is for both graduate and undergraduate students that have special interests on Deep Learning (DL). In this seminar series, the students will collaborate in an intensive examination of topics related to understanding the basic concepts, models and algorithms of DL. The basic module of the Deep Learning seminar is designed as a discussion seminar. Emphasis will be on close reading and discussion of the assigned readings. Each volunteer participant will be responsible for leading the seminar discussion on assigned weeks. All participants are expected to come prepared to discuss and debate the readings each week. Participants will develop their understanding of the material through class presentations and discussions. An advanced module of source code review is designed for the participants that want to develop their skills on implementing existing DL models and designing new models. Emphasis will be on close review and discussion of the DL models. Each participant will be responsible for leading the seminar discussion on mathematic formulas, algorithms and the source code of the assigned model. In particular, this seminar will use Apache SINGA (http://singa.apache.org/), an open source DL platform for code review.

0 comments    
12575 Deep Learning libraries
(20887 libraries)
Go
(96513 libraries)
(52487 libraries)
(17370 libraries)
(29243 libraries)
C#
(46701 libraries)
(24431 libraries)
(44200 libraries)
(14302 libraries)
(10317 libraries)
(25386 libraries)
(16473 libraries)
(164666 libraries)
(15909 libraries)
Vue
(15682 libraries)
CSS
(77934 libraries)
(73849 libraries)
(59699 libraries)
(12575 libraries)
C++
(100016 libraries)
C
(82327 libraries)
(48369 libraries)
(44636 libraries)
(11027 libraries)
(68285 libraries)
PHP
(101446 libraries)
(131176 libraries)
(143433 libraries)
(6843 libraries)
Nim
(4514 libraries)
D
(11427 libraries)
(41169 libraries)
(2705 libraries)