Search Results for "python 3.5 library"
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Showing 23 open source projects for "python 3.5 library"
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MegEngine
Easy-to-use deep learning framework with 3 key features
...In training, GPU memory usage could go down to one-third at the cost of only one additional line, which enables the DTR algorithm. Gain the lowest memory usage when inferencing a model by leveraging our unique pushdown memory planner. NOTE: MegEngine now supports Python installation on Linux-64bit/Windows-64bit/MacOS(CPU-Only)-10.14+/Android 7+(CPU-Only) platforms with Python from 3.5 to 3.8. On Windows 10 you can either install the Linux distribution through Windows Subsystem for Linux (WSL) or install the Windows distribution directly. Many other platforms are supported for inference. -
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Pedalboard
A Python library for audio
pedalboard is a Python library for working with audio: reading, writing, rendering, adding effects, and more. It supports the most popular audio file formats and a number of common audio effects out of the box and also allows the use of VST3® and Audio Unit formats for loading third-party software instruments and effects. pedalboard was built by Spotify’s Audio Intelligence Lab to enable using studio-quality audio effects from within Python and TensorFlow. -
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OpenCV
Open Source Computer Vision Library
OpenCV (Open Source Computer Vision Library) is a comprehensive open-source library for computer vision, machine learning, and image processing. It enables developers to build real-time vision applications ranging from facial recognition to object tracking. OpenCV supports a wide range of programming languages including C++, Python, and Java, and is optimized for both CPU and GPU operations. -
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TensorFlow
TensorFlow is an open source library for machine learning
Originally developed by Google for internal use, TensorFlow is an open source platform for machine learning. Available across all common operating systems (desktop, server and mobile), TensorFlow provides stable APIs for Python and C as well as APIs that are not guaranteed to be backwards compatible or are 3rd party for a variety of other languages. The platform can be easily deployed on multiple CPUs, GPUs and Google's proprietary chip, the tensor processing unit (TPU). TensorFlow... -
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CatBoost
High-performance library for gradient boosting on decision trees
CatBoost is a fast, high-performance open source library for gradient boosting on decision trees. It is a machine learning method with plenty of applications, including ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. CatBoost offers superior performance over other GBDT libraries on many datasets, and has several superb features. It has best in class prediction speed, supports both numerical and categorical features, has a fast and scalable GPU version, and readily comes with visualization tools. ... -
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mlpack
mlpack: a scalable C++ machine learning library
mlpack is an intuitive, fast, and flexible C++ machine learning library with bindings to other languages. It is meant to be a machine learning analog to LAPACK, and aims to implement a wide array of machine learning methods and functions as a "swiss army knife" for machine learning researchers. In addition to its powerful C++ interface, mlpack also provides command-line programs, Python bindings, Julia bindings, Go bindings and R bindings. -
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eos
A lightweight 3D Morphable Face Model library in modern C++
eos is a lightweight 3D Morphable Face Model fitting library that provides basic functionality to use face models, as well as camera and shape fitting functionality. It's written in modern C++11/14. MorphableModel and PcaModel classes to represent 3DMMs, with basic operations like draw_sample(). Supports the Surrey Face Model (SFM), 4D Face Model (4DFM), Basel Face Model (BFM) 2009 and 2017, and the Liverpool-York Head Model (LYHM) out-of-the-box. -
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DALI
A GPU-accelerated library containing highly optimized building blocks
The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provides a collection of highly optimized building blocks for loading and processing image, video and audio data. It can be used as a portable drop-in replacement for built-in data loaders and data iterators in popular deep learning frameworks. Deep learning applications require complex, multi-stage data processing pipelines that include loading, decoding,... -
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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. -
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OpenSpiel
Environments and algorithms for research in general reinforcement
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games. OpenSpiel supports n-player (single- and multi- agent) zero-sum, cooperative and general-sum, one-shot and sequential, strictly turn-taking and simultaneous-move, perfect and imperfect information games, as well as traditional multiagent environments such as (partially- and fully- observable) grid worlds and social dilemmas. OpenSpiel also includes tools to... -
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cuML
RAPIDS Machine Learning Library
cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn. For large datasets, these GPU-based implementations can complete 10-50x faster than their CPU... -
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads:... -
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Uranie
Uranie is CEA's uncertainty analysis platform, based on ROOT
Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is... -
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SMILI
Scientific Visualisation Made Easy
The Simple Medical Imaging Library Interface (SMILI), pronounced 'smilie', is an open-source, light-weight and easy-to-use medical imaging viewer and library for all major operating systems. The main sMILX application features for viewing n-D images, vector images, DICOMs, anonymizing, shape analysis and models/surfaces with easy drag and drop functions. It also features a number of standard processing algorithms for smoothing, thresholding, masking etc. images and models, both with... -
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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TensorRT Pro
C++ library based on tensorrt integration
High-level interface for C++/Python. Simplify the implementation of the custom plugin. And serialization and deserialization have been encapsulated for easier usage. Simplify the compilation of fp32, fp16 and int8 for facilitating the deployment with C++/Python in server or embedded device. Models ready for use also with examples are RetinaFace, Scrfd, YoloV5, YoloX, Arcface, AlphaPose, CenterNet and DeepSORT(C++). -
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BlazingSQL
BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python
BlazingSQL is a GPU-accelerated SQL engine built on top of the RAPIDS ecosystem. RAPIDS is based on the Apache Arrow columnar memory format, and cuDF is a GPU DataFrame library for loading, joining, aggregating, filtering, and otherwise manipulating data. BlazingSQL is a SQL interface for cuDF, with various features to support large-scale data science workflows and enterprise datasets. -
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wav2letter++
Facebook AI research's automatic speech recognition toolkit
First, install Flashlight (using the 0.3 branch is required) with the ASR application. This repository includes recipes to reproduce the following research papers as well as pre-trained models. All results reproduction must use Flashlight <= 0.3.2 for exact reproducibility. At least one of LZMA, BZip2, or Z is required for LM compression with KenLM. It is highly recommended to build KenLM with position-independent code (-fPIC) enabled, to enable python compatibility. After installing, run... -
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Turi Create
Simplifies the development of custom machine learning models
...If you want your app to recognize specific objects in images, you can build your own model with just a few lines of code. Turi Create supports macOS 10.12+, Linux (with glibc 2.10+), Windows 10 (via WSL). Turi Create requires Python 2.7, 3.5, 3.6, 3.7, 3.8. Also, x86_64 architecture, and at least 4 GB of RAM. We recommend using virtualenv to use, install, or build Turi Create. The package User Guide and API Docs contain more details on how to use Turi Create. If you want to build Turi Create from source, see BUILD.md. Turi Create does not require a GPU, but certain models can be accelerated 9-13x by utilizing a GPU. -
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xLearn
High performance, easy-to-use, and scalable machine learning (ML)
xLearn is a high-performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM), all of which can be used to solve large-scale machine learning problems. xLearn is especially useful for solving machine learning problems on large-scale sparse data. Many real-world datasets deal with high dimensional sparse feature vectors like a recommendation system where the number of categories and... -
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TorchCraft
Connecting Torch to StarCraft
...This lets you parse StarCraft data and interact with BWAPI from anywhere. The TorchCraft client should be installed from C++, Python, or Lua. We provide off-the-shelf solutions for Python and Lua. -
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OpenANN
An open source library for artificial neural networks.
OpenANN is a C++ library that provides implementations for modular artificial neural networks with only a few dependencies and additional Python bindings. -
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Yann is Yet Another Neural Network. Yann is a library to create fast neural networks. It is also a GUI to easily create, edit, train, execute and investigate networks. Multiple topologies, runtime properties and ensemble learning are supported.
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