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deeplearning4j
D
Analyzed about 5 hours ago
Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library; designed to be used in business environments.
Deeplearning4j aims to be cutting-edge plug and play, more convention than configuration, which allows for fast prototyping for non-researchers.
Vast
Licenses:
apache_2
The ADAMS Flow
Analyzed about 6 hours ago
ADAMS is a flexible workflow engine aimed at quickly building and maintaining data-driven, reactive workflows, easily integrated into business processes.
Instead of placing operators on a canvas and manually connecting them, a tree structure and flow control operators determine how data is
Licenses:
gpl3_or_l...
word2vec-query-expansion
W
Analyzed about 16 hours ago
An Apache Lucene TokenFilter that uses a word2vec vectors for term expansion.
Licenses:
apache_2
Neural Audio Fingerprint
N
Analyzed about 10 hours ago
This is an official code and dataset release by authors (since July 2021) for reproducing "Neural Audio Fingerprint for High-specific Audio Retrieval based on Contrastive Learning" ICASSP 2021
libdeep
No analysis available
This is a C library which can be used in deep learning applications. What differentiates libdeep from the numerous other deep learning systems out there is that it's small and that trained networks can be exported as completely standalone C or Python programs which can either be used via the
Mostly written in language not available
Licenses:
BSD-3-Clause
AIJack
Analyzed about 11 hours ago
Security and Privacy Risk Simulator for Machine Learning
AIJack is an open source tool that helps you identify and protect against security and privacy attacks on machine learning algorithms. It includes defense techniques like Differential Privacy and Homomorphic Encryption, as well as APIs for
Licenses:
apache_2
Savant
S
No analysis available
Python Computer Vision & Video Analytics Framework With Batteries Included
Mostly written in language not available
Licenses:
apache_v2
CNTK
C
Analyzed 15 minutes ago
CNTK (Computational Network Toolkit) by Microsoft Research, is a unified deep-learning toolkit that describes neural networks as a series of computational steps via a directed graph. In this directed graph, leaf nodes represent input values or network parameters, while other nodes represent matrix
Licenses:
No declared licenses
tiny-cnn
T
Analyzed about 20 hours ago
header only, dependency-free deep learning framework in C++11
Licenses:
No declared licenses