kann
Genann
kann | Genann | |
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5 | 7 | |
656 | 1,905 | |
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0.0 | 0.0 | |
over 2 years ago | 8 months ago | |
C | C | |
GNU General Public License v3.0 or later | zlib License |
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kann
- Small tensor library in C99
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C with Deep Learning
TensorFlow has C APIs. I developed KANN from scratch for deep learning. It supports CNN, LSTM and complex topologies. For simple MLPs, you can implement your own as a practice. Use a BLAS library for performance.
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Implementing Faster R-CNN in C
After some research, I have reached the conclusion that I should use Faster R-CNN. So far, I have completed a classification task with a basic CNN using the C Kann library, as it can create basic layers and has basic functionalities..
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Using Kann library to classify color images with a CNN
I'm trying to use the kann library to create a model that classifies color images using a CNN, following the mnist cnn example.
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C Deep
KANN - Two-file ANN library. MIT
Genann
- Simple neural network library in ANSI C
- Genann: Simple neural network library in ANSI C
- Machine learning Library in C?
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Ask HN: What ML platform are you using?
> I am very much a beginner in the space of machine learning
While the (precious and useful) advice around seem to cover mostly the bigger infrastructures, please note that
you can effectively do an important slice of machine learning work (study, personal research) with just a battery-efficiency-level CPU (not GPU), in the order of minutes, on a battery. That comes before going to "Big Data".
And there are lightweight tools: I am current enamoured with Genann («minimal, well-tested open-source library implementing feedfordward artificial neural networks (ANN) in C»), a single C file of 400 lines compiling to a 40kb object, yet well sufficient to solve a number of the problems you may meet.
https://codeplea.com/genann // https://github.com/codeplea/genann
After all, is it a good idea to have tools that automate process optimization while you are learning the deal? Only partially. You should build - in general and even metaphorically - the legitimacy of your Python ops on a good C ground.
And: note that you can also build ANNs in R (and other math or stats environments). If needed or comfortable...
Also note - reminder - that the MIT lessons of Prof. Patrick Winston for the Artificial Intelligence course (classical AI with a few lessons on ANNs) are freely available. That covers the grounds relative to climb into the newer techniques.
- Small tensor library in C99
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C Deep
Genann - Simple ANN in C89, without additional dependencies. Zlib
What are some alternatives?
ZLib - A massively spiffy yet delicately unobtrusive compression library.
tiny-cnn - header only, dependency-free deep learning framework in C++14
darknet - Convolutional Neural Networks
Recast/Detour - Industry-standard navigation-mesh toolset for games
tensorflow - An Open Source Machine Learning Framework for Everyone
frugally-deep - Header-only library for using Keras (TensorFlow) models in C++.
GLFW - A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input
Redis - Redis is an in-memory database that persists on disk. The data model is key-value, but many different kind of values are supported: Strings, Lists, Sets, Sorted Sets, Hashes, Streams, HyperLogLogs, Bitmaps.
ANNetGPGPU - A GPU (CUDA) based Artificial Neural Network library
MIRACL - MIRACL Cryptographic SDK: Multiprecision Integer and Rational Arithmetic Cryptographic Library is a C software library that is widely regarded by developers as the gold standard open source SDK for elliptic curve cryptography (ECC).
BayesOpt - BayesOpt: A toolbox for bayesian optimization, experimental design and stochastic bandits.