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Showing 16 open source projects for "type"
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ONNX
Open standard for machine learning interoperability
ONNX is an open format built to represent machine learning models. ONNX defines a common set of operators - the building blocks of machine learning and deep learning models - and a common file format to enable AI developers to use models with a variety of frameworks, tools, runtimes, and compilers. Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both... -
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GoogleTest
Google Testing and Mocking Framework
GoogleTest is Google's C++ mocking and test framework. It's used by many internal projects at Google, as well as a number of notable projects such as The Chromium projects, the OpenCV computer vision library, and the LLVM compiler. This GoogleTest project is actually a union of what used to be two separate projects: the old GoogleTest and GoogleMock, an extension of GoogleTest for writing and using C++ mock classes. Since they were so closely related, they were merged to create an even... -
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DataFrame
C++ DataFrame for statistical, Financial, and ML analysis
This is a C++ analytical library designed for data analysis similar to libraries in Python and R. For example, you would compare this to Pandas, R data.frame, or Polars. You can slice the data in many different ways. You can join, merge, and group-by the data. You can run various statistical, summarization, financial, and ML algorithms on the data. You can add your custom algorithms easily. You can multi-column sort, custom pick, and delete the data. DataFrame also includes a large... -
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Evolutionary Computation Framework
C++ framework for application of any type of evolutionary computation.
ECF is a framework intended for application of any type of evolutionary computation (GA/GP, DE, Clonalg, ES, PSO, ABC, GAn, local search...). It offers simplicity for the end-user (parameterless usage, tutorial) and customization for experienced EC practicioners. -
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OnnxStream
Lightweight inference library for ONNX files, written in C++
...OnnxStream is based on the idea of decoupling the inference engine from the component responsible for providing the model weights, which is a class derived from WeightsProvider. A WeightsProvider specialization can implement any type of loading, caching, and prefetching of the model parameters. -
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Alpaca.cpp
Locally run an Instruction-Tuned Chat-Style LLM
Run a fast ChatGPT-like model locally on your device. This combines the LLaMA foundation model with an open reproduction of Stanford Alpaca a fine-tuning of the base model to obey instructions (akin to the RLHF used to train ChatGPT) and a set of modifications to llama.cpp to add a chat interface. Download the zip file corresponding to your operating system from the latest release. The weights are based on the published fine-tunes from alpaca-lora, converted back into a PyTorch checkpoint... -
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Euler
A distributed graph deep learning framework.
As a general data structure with strong expressive ability, graphs can be used to describe many problems in the real world, such as user networks in social scenarios, user and commodity networks in e-commerce scenarios, communication networks in telecom scenarios, and transaction networks in financial scenarios. and drug molecule networks in medical scenarios, etc. Data in the fields of text, speech, and images is easier to process into a grid-like type of Euclidean space, which is suitable for processing by existing deep learning models. Graph is a data type in non-Euclidean space and cannot be directly applied to existing methods, requiring a specially designed graph neural network system. Graph-based learning methods such as graph neural networks combine end-to-end learning with inductive reasoning, and are expected to solve a series of problems such as relational reasoning and interpretability that deep learning cannot handle. -
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ChordEase
Improvise to music with difficult chords easily on any MIDI instrument
...No matter what the chords are, you can play as if they were all in the key of C. You don't need to play sharps or flats, because ChordEase automatically adds them for you. Though ChordEase is intended for jazz, it could be useful for any type of music that modulates frequently. ChordEase alters your notes in real time in order to make them harmonically correct, while preserving their rhythm and dynamics. By delegating rapid music theory calculations to ChordEase, you gain freedom to concentrate on other aspects of improvisation and performance, such as feel and aesthetics. ... -
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PartWriter
A project designed to write sheet music.
...The first layer is an artificial intelligence engine, partwriter, that writes music based on some heuristic. The second layer is the layer that defines the heuristic. The definition of this heuristic defines the type of music that partwriter will create. Currently (December 2012), the deepest layer is more or less complete. The author is now writing second layers of interest, namely species counterpoint heuristics according to Fux's Gradus Ad Parnassum. -
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EasyCP
The easiest C++ way to deal with constraints !
EasyCP is a modern, user-friendly C++ library that lets you use constraint programming in a very natural way, taking advantage of its expressive power. Just model and let the CSP (Constraint Satisfaction Problem) solver do the job ! -
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QVision: Computer Vision Library for Qt
Computer vision and image processing library for Qt.
This library contains among other things a set of graphical widgets for video output, performance evaluation and augmented reality. The library also provides classes for several data types usually required by computer vision and image processing applications such as vectors, matrices, quaternions and images. Thanks to a large number of wrapper functions these objects can be used with highly efficient functionality from third party libraries such as OpenCV, GNU Scientific Library,... -
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It's an object-oriented library written in C++ for creating arbitrary kind of neural networks. The user can use the classes provided to create neural network with arbitrary topology and mixed type of neurons. It's very easy add custom neurons.
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This is a T2S or "Text To Speech" application that will allow Mac OS X 10.5 users to type in any text into the text box then hear it.
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QUANTBOOST, a Complete Library, Modelling of Derivatives in C++. Based on Wiley C++ Derivatives, as well as BOOST C++ Multithreading techniques and will support a quant fund approach type of forecasting and portfolio management. I will have direct access
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j4cEvo is an open source java api that allows to program an artificial intelligence for a civilization type public domain game called civ evolution.
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This is proof-of-concept type of project with not much to look at yet. I'm checking some ideas I find interesting about neural nets and genetic algorithms.
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