Nerve
Genann
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Nerve
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[Hobby] I Need a Friendly Team. Your Experience Doesn't Matter!
Nerve (Neural Network Library) : https://github.com/fkkarakurt/Nerve
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Nerve | Neural Network Library
Did you find the short and concise documentation at https://github.com/fkkarakurt/Nerve/wiki insufficient? If so, I might consider making some improvements to it.
GITHUB REPO => https://github.com/fkkarakurt/Nerve WIKI => https://github.com/fkkarakurt/Nerve/wiki STRUCTURE => https://github.com/fkkarakurt/Nerve#internal-structure
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?
ruby-fann - Ruby library for interfacing with FANN (Fast Artificial Neural Network)
tiny-cnn - header only, dependency-free deep learning framework in C++14
sod - An Embedded Computer Vision & Machine Learning Library (CPU Optimized & IoT Capable)
Recast/Detour - Industry-standard navigation-mesh toolset for games
iNeural - A library for creating Artificial Neural Networks, for use in Machine Learning and Deep Learning algorithms.
frugally-deep - Header-only library for using Keras (TensorFlow) models in C++.
artificial-intelligence-and-machine-learning - A repository for implementation of artificial intelligence algorithm which includes machine learning and deep learning algorithm as well as classical AI search algorithm
tensorflow - An Open Source Machine Learning Framework for Everyone
igel - a delightful machine learning tool that allows you to train, test, and use models without writing code
ANNetGPGPU - A GPU (CUDA) based Artificial Neural Network library
paramonte - ParaMonte: Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C.
BayesOpt - BayesOpt: A toolbox for bayesian optimization, experimental design and stochastic bandits.