Are you looking for an open source neural network project? In this article you will find those projects and links to access the code in GitHub. Let’s take a tour of the top 20 open source neural network projects.
TensorFlow is an open-source project used in machine learning. It contains a complete, adjustable environs of libraries, tool and community assets that allow analyzers push the ultra-modern ML, and it becomes easy for constructors to build and install ML-driven applications. It supplies stable C++ and Python API and also uncollateralized backward well-suited API used with other languages.
PyTorch is a python collection that gives 2 high level characteristics
You can utilize your treasured Python packages like SciPy, Cython, and NumPy to lengthen PyTorch when required.
Accord.NET project gives machine learning, artificial intelligence, image processing, statistics and computer vision techniques to .NET. You can use it on Microsoft Windows, Unity3D, Xamarin, mobile, or Windows store apps. Accord.NET supports logistic regression, vector machines, neural networks, decision trees, and deep learning. After amalgamation with Project AForge.NET, it now provides a unified API uses in training/learning machine learning framework that is extensible and easy to use.
Cellular Neural Networks are an analogous computing paradigm they are the same with neural networks with only one difference that information exchange is restricted to neighboring units. CNN processors are utilized in image processing. They were modelled to carry out image processing I.e., instantaneous ultra-high-frame-rate (10,00 frames) which could not be achieved by the digital processors.
Encog is a machine learning structure that supports pure C#/Java. Its neural network features were well known, and it was utilized by many persons. The fact that it’s created with pure Java, makes it easy to remodel and use it when you are creating a neural network from scratch. It supports advanced some algorithms and also does aid classes to standardize and process figures.
GluonCV gives fulfillment of futuristic deep learning framework in computer perception. It is constructed for students, researchers and engineers for speedy research ideas and prototype products established on those designs. Its toolkit contains the following features
Gorgonia is a collection that facilitates machine learning in Go. It is similar to Tensor-flow or Theano, and this library is a low-level library just like Theano while it has more great goals like TensorFlow. Features
Seq2seq is a universal encoder-decoder structure for TensorFlow that is used for text summarization, machine translation, image captioning and conversational modeling. It was designed to fulfill the following goals:
Chainer it’s a deep learning structure which is Python-based, and it aims at being flexible. It has unmanned differentiation APIs according to dynamic computation graphs. It also has object-oriented top tier APIs for constructing and training neural networks. CLICK FOR MORE DETAILS
BigDL is a scattered rooted learning collection for Apache Spark. It allows you to code rooted learning apps like normal Spark programs, and it has the ability to run over existing Hadoop or Spark clusters. Features
Open Neural Network Exchange is an unlocked environ that empowers Artificial Intelligence you to select the proper tools as your project evolves. It gives an open-source design for AI designs, traditional ML and deep learning. It defines normal data types, inbuilt operators and extendable computation graph model. It is supported widely, and it’s found on different tools, hardware and frameworks this enhances compatibility between non-identical frameworks.
SpaCY is a collection for modern natural language processing in Cython and Python. It is designed using real world products and constructed on modern research. It has inbuilt pretrained pipelines, training for over 60 languages and supports tokenization. It has futuristic neural network models and speed for parsing, tagging, multitask learning, text classification and named entity recognition. CLICK FOR MORE DETAILS
TFLearn is a transparent and modular rooted learning collection constructed above TensorFlow. It gives a higher-level API to TensorFlow for it to help accelerate experimentation Features:
ML5 is a social machine learning used for web. Its goal is to make machine learning welcoming for a large audience of creative coders, students and artists. It gives entry to machine learning models and algorithms in the browser constructed above TensorFlow.js.
Genann is a negligible wee-testes collection used to train and feed forwarding unnatural neural networks in C. Features
FANN a free neural network collection that performs layered artificial neural networks in C and supports scant and fully connected networks. It binds to over 15 programming languages and has a couple of graphical user interfaces. Features
Tiny-dnn is a C++ 14 administration of deep learning. It is good for rooted learning on restricted embedded systems, IoT services and computational resource. Features
NiftyNet is a Tensorlow established open-source complex neural networks programme for researching in image-guided therapy and medical image investigation. Its modular constitution is designed for dividing networks and pretrained models. Features
CLgen is a free application for coming up with executable programs using rooted (deep) learning. It learns to program by utilizing neural networks that design the semantics and utilization from huge volumes of program bits. It produces numerous-core OpenCL programs that represent the learned program, but it is different from it
The above are the top best neural network projects that you can access on GitHub to do deep learning. What you need to do is just choose one that suits your needs.
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