Search Results for "library python" - Page 2
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Showing 121 open source projects for "library python"
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nb-clean
Clean Jupyter notebooks of outputs, metadata, and empty cells
...It provides both a Git filter and pre-commit hook to automatically clean notebooks before they're staged, and can also be used with other version control systems, as a command line tool, and as a Python library. It can determine if a notebook is clean or not, which can be used as a check in your continuous integration pipelines. nb-clean can also be used as a pre-commit hook. You may prefer this to the Git filter if your project already uses the pre-commit framework. Note that the Git filter and pre-commit hook work differently, with different effects on your working directory. ... -
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XGBoost
Scalable and Flexible Gradient Boosting
...XGBoost can be used for Python, Java, Scala, R, C++ and more. It can run on a single machine, Hadoop, Spark, Dask, Flink and most other distributed environments, and is capable of solving problems beyond billions of examples. -
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KubeRay
A toolkit to run Ray applications on Kubernetes
KubeRay is a powerful, open-source Kubernetes operator that simplifies the deployment and management of Ray applications on Kubernetes. It offers several key components. KubeRay core: This is the official, fully-maintained component of KubeRay that provides three custom resource definitions, RayCluster, RayJob, and RayService. These resources are designed to help you run a wide range of workloads with ease. -
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NannyML
Detecting silent model failure. NannyML estimates performance
NannyML is an open-source python library that allows you to estimate post-deployment model performance (without access to targets), detect data drift, and intelligently link data drift alerts back to changes in model performance. Built for data scientists, NannyML has an easy-to-use interface, and interactive visualizations, is completely model-agnostic, and currently supports all tabular classification use cases. -
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CxxWrap
Package to make C++ libraries available in Julia
This package aims to provide a Boost. Python-like wrapping for C++ types and functions to Julia. The idea is to write the code for the Julia wrapper in C++, and then use a one-liner on the Julia side to make the wrapped C++ library available there. The mechanism behind this package is that functions and types are registered in C++ code that is compiled into a dynamic library. -
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SDGym
Benchmarking synthetic data generation methods
The Synthetic Data Gym (SDGym) is a benchmarking framework for modeling and generating synthetic data. Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking. You also customize the process to include your own work. Select any of the publicly available datasets from the... -
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gramm
Gramm is a complete data visualization toolbox for Matlab
...Its design philosophy focuses on a declarative approach, where users specify the desired end result, as opposed to the traditional imperative method involving for loops, if/else statements, etc. The MATLAB implementation of gramm is inspired by the "grammar of graphics" principles (Wilkinson 1999) and the ggplot2 library for R by Hadley Wickham. As a reference to this inspiration, gramm stands for GRAMmar of graphics for MATLAB. A similar library called Seaborn also exists for Python. Gramm has been used in many publications from varied fields and is particularily suited for neuroscience, from human movement psychophysics (Morel et al. 2017), to electrophysiology (Morel et al. 2016; Ferrea et al. 2017), human functional imaging (Wan et al. 2017) and animal training (Berger et al. 2017). -
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Siddhi Core Libraries
Stream Processing and Complex Event Processing Engine
Fully open source, cloud-native, scalable, micro streaming, and complex event processing system capable of building event-driven applications for use cases such as real-time analytics, data integration, notification management, and adaptive decision-making. Event processing logic can be written using Streaming SQL queries via graphical and source editors, to capture events from diverse data sources, process and analyze them, integrate with multiple services and data stores, and publish... -
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SageMaker Training Toolkit
Train machine learning models within Docker containers
Train machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and... -
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NBInclude.jl
import code from IJulia Jupyter notebooks into Julia programs
NBInclude is a package for the Julia language that allows you to include and execute IJulia (Julia-language Jupyter) notebook files just as you would include an ordinary Julia file. The goal of this package is to make notebook files just as easy to incorporate into Julia programs as ordinary Julia (.jl) files, giving you the advantages of a notebook (integrated code, formatted text, equations, graphics, and other results) while retaining the modularity and re-usability of .jl files. -
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Synapse Machine Learning
Simple and distributed Machine Learning
SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. SynapseML builds on Apache Spark and SparkML to enable new kinds of machine learning, analytics, and model deployment workflows. SynapseML adds many deep learning and data science tools to the Spark ecosystem, including seamless integration of Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit,... -
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NVIDIA Merlin
Library providing end-to-end GPU-accelerated recommender systems
NVIDIA Merlin is an open-source library that accelerates recommender systems on NVIDIA GPUs. The library enables data scientists, machine learning engineers, and researchers to build high-performing recommenders at scale. Merlin includes tools to address common feature engineering, training, and inference challenges. Each stage of the Merlin pipeline is optimized to support hundreds of terabytes of data, which is all accessible through easy-to-use APIs. For more information, see NVIDIA... -
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MathGL
A library for scientific data visualization
A free cross-platform library of fast C++ routines for the plotting of up to 3-ranged data. It can export to bitmap and vector EPS/SVG files. There are window interfaces (GLUT/FLTK/Qt) and console tools. MathGL can be used from C/Fortran/Python/Octav/Lua -
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PLplot
Cross-platform, scientific graphics plotting library
PLplot is a cross-platform, scientific graphics plotting library that supports math symbols and human languages (via UTF-8 user input strings); plot capabilities for multiple non-interactive plot file formats and in multiple interactive environments; and bindings for multiple computer languages. -
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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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xrayutilities
a package with useful scripts for X-ray diffraction physicists
xrayutilities is a python package used to analyze x-ray diffraction data. It can support with performing diffraction experiments and used for common steps in the data analysis. It can read experimental data from several data formats (spec, edf, xrdml, ...); convert them to reciprocal space for arbitrary goniometer geometries and different detector systems (point, linear as well as area detectors); for further processing the data can be gridded (transformed to a regular grid). More... -
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Datapipe
Real-time, incremental ETL library for ML with record-level depend
Datapipe is a real-time, incremental ETL library for Python with record-level dependency tracking. Datapipe is designed to streamline the creation of data processing pipelines. It excels in scenarios where data is continuously changing, requiring pipelines to adapt and process only the modified data efficiently. This library tracks dependencies for each record in the pipeline, ensuring minimal and efficient data processing. -
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A python-based system to diagnosis and make weather maps (wxmap) of numerical weather prediction models using the Grid Analysis and Display System (GrADS) from opengrads.org
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OpenPTV
OpenPTV
OpenPTV is an abbreviation of the open source particle tracking velocimetry. This is an open source framework, developed jointly by academic institutions, that deals primarily with the three-dimensional particle tracking experiments in complex and turbulent flows. More about 3D-PTV on Wikipedia and links from our website: http://www.openptv.net -
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MCPower
MCPower — simple Monte Carlo power analysis for complex models
MCPower-GUI is a desktop application that provides a graphical interface for the MCPower Monte Carlo power analysis library. It guides users through the full workflow across three tabs: Model setup (formula input with live parsing, CSV data upload with auto-detected variable types, effect size sliders, and correlation editing), Analysis configuration (find power for a given sample size or find the minimum sample size for a target power, with multiple testing correction and scenario analysis), and Results (interactive charts, exportable tables, and auto-generated Python replication scripts). ... -
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FreeImage is a library project for developers who would like to support popular graphics image formats (PNG, JPEG, TIFF, BMP and others). Some highlights are: extremely simple in use, not limited to the local PC (unique FreeImageIO) and Plugin driven!
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seaborn
Statistical data visualization in Python
Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Seaborn helps you explore and understand your data. Its plotting functions operate on dataframes and arrays containing whole datasets and internally perform the necessary semantic mapping and statistical aggregation to produce informative plots. -
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libCEED
CEED Library: Code for Efficient Extensible Discretizations
libCEED provides fast algebra for element-based discretizations, designed for performance portability, run-time flexibility, and clean embedding in higher-level libraries and applications. It offers a C99 interface as well as bindings for Fortran, Python, Julia, and Rust. While our focus is on high-order finite elements, the approach is mostly algebraic and thus applicable to other discretizations in factored form, as explained in the user manual and API implementation portion of the... -
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SageMaker Inference Toolkit
Serve machine learning models within a Docker container
Serve machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. Once you have a trained model, you can include it in a Docker container that runs your inference code. A container provides an effectively isolated environment, ensuring a consistent runtime regardless of where the... -
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text-dedup
All-in-one text de-duplication
text-dedup is a Python library that enables efficient deduplication of large text corpora by using MinHash and other probabilistic techniques to detect near-duplicate content. This is especially useful for NLP tasks where duplicated training data can skew model performance. text-dedup scales to billions of documents and offers tools for chunking, hashing, and comparing text efficiently with low memory usage.