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Showing 29 open source projects for "improve"
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Our service seals applications with runtime application self-protection features in minutes without writing a single line of code. The service comes with a real-time monitoring dashboard which tracks the hacking attempts and delivers smart reports to make complex decisions. AppSealing provides Runtime Application Self protection (RASP) against hackers who are looking to clone, tamper, inject malicious code, or in general exploit your mobile app.
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Diffgram
Training data (data labeling, annotation, workflow) for all data types
From ingesting data to exploring it, annotating it, and managing workflows. Diffgram is a single application that will improve your data labeling and bring all aspects of training data under a single roof. Diffgram is world’s first truly open source training data platform that focuses on giving its users an unlimited experience. This is aimed to reduce your data labeling bills and increase your Training Data Quality. Training Data is the art of supervising machines through data. This includes... -
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React Chart.js
React components for Chart.js, the most popular charting library
React components for Chart.js, the most popular charting library. With v4, this library introduces a number of breaking changes. In order to improve performance, offer new features, and improve maintainability, it was necessary to break backwards compatibility, but we aimed to do so only when worth the benefit. You will find that any event which causes the chart to re-render, such as hover tooltips, etc., will cause the first dataset to be copied over to other datasets, causing your lines... -
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Mousetrap.jl
Finally, a GUI Engine made for Julia
Mousetrap is a GUI library designed for Julia. It fully wraps GTK4 (which is written in C), vastly simplifying its interface to improve ease of use without sacrificing flexibility. It aims to give developers of all skill levels the tools to start creating complex GUI applications with little time and effort while taking full advantage of Julia's idiosyncrasies. -
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Gretel Synthetics
Synthetic data generators for structured and unstructured text
Unlock unlimited possibilities with synthetic data. Share, create, and augment data with cutting-edge generative AI. Generate unlimited data in minutes with synthetic data delivered as-a-service. Synthesize data that are as good or better than your original dataset, and maintain relationships and statistical insights. Customize privacy settings so that data is always safe while remaining useful for downstream workflows. Ensure data accuracy and privacy confidently with expert-grade reports.... -
QuickBooks Online makes accounting easy. Make tracking receipts, income, bank transactions, and more feel simple with the #1 small business accounting software. Snap photos of your receipts and link them to expenses right from your phone. Our agents are ready and available to answer all your QuickBooks questions. Use the apps you know and love to keep your business running smoothly. QuickBooks Online works on your PC, Mac, tablets, and phones.
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PowerSimulationsDynamics.jl
Julia package to run Dynamic Power System simulations
PowerSimulationsDynamics.jl is a Julia package for power system modeling and simulation of Power Systems dynamics. -
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Alova.js
Workflow-Streamlined next-generation request tools
Extremely streamline API integration workflow. Quickly find APIs in the editor, and enjoy full type hints even in js projects with the API code automatically generated by Alova's extension. Request in various complex scenes by one line of code. Automatically manage paging data, and data preloading, reduce unnecessary data refresh, improve fluency by 300%, and reduce coding difficulty by 50%. Send requests immediately by watching state changes, useful in tab switching and condition querying... -
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PowerSimulations.jl
Julia for optimization simulation and modeling of PowerSystems
PowerSimulations.jl is a Julia package for power system modeling and simulation of Power Systems operations. Provide a flexible modeling framework that can accommodate problems of different complexity and at different time scales. Streamline the construction of large-scale optimization problems to avoid repetition of work when adding/modifying model details. Exploit Julia's capabilities to improve computational performance of large-scale power system quasi-static simulations. The flexible... -
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Fluid
Fluid, elastic data abstraction and acceleration for BigData/AI apps
Fluid, elastic data abstraction and acceleration for BigData/AI applications in the cloud. Provide DataSet abstraction for underlying heterogeneous data sources with multidimensional management in a cloud environment. Enable dataset warmup and acceleration for data-intensive applications by using a distributed cache in Kubernetes with observability, portability, and scalability. Taking characteristics of application and data into consideration for cloud application/dataset scheduling to improve... -
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DynamicQuantities.jl
Lightweight + fast physical quantities in Julia
DynamicQuantities defines a simple statically-typed Quantity type for Julia. Physical dimensions are stored as a value, as opposed to a parametric type, as in Unitful.jl. This can greatly improve both runtime performance, by avoiding type instabilities, and startup time, as it avoids overspecializing methods. -
For easy and transparent time and attendance tracking, trust in ITCS-WebClock. ITCS-WebClock is an online time and attendance system that helps companies and managers track employees' time and attendance information from anywhere. The system comes with rich reporting and automation tools, expense management, absence management, and employee scheduling tools, as well as PEO and payroll integrations.
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airda
airda(Air Data Agent
airda(Air Data Agent) is a multi-smart body for data analysis, capable of understanding data development and data analysis needs, understanding data, generating data-oriented queries, data visualization, machine learning and other tasks of SQL and Python codes. -
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SciML Style Guide for Julia
A style guide for stylish Julia developers
... recommended functionality should be tested, and any known generality issues should be documented in an issue (and with a @test_broken test when possible). However, a function that is known to not be GPU-compatible is not grounds to block merging, rather it is encouraged for a follow-up PR to improve the general type support. -
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DataQualityDashboard
A tool to help improve data quality standards in data science
The goal of the Data Quality Dashboard (DQD) project is to design and develop an open-source tool to expose and evaluate observational data quality. This package will run a series of data quality checks against an OMOP CDM instance (currently supports v5.4, v5.3 and v5.2). It systematically runs the checks, evaluates the checks against some pre-specified threshold, and then communicates what was done in a transparent and easily understandable way. The quality checks were organized according... -
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Phoenix
Uncover insights, surface problems, monitor, and fine tune your LLM
Phoenix provides ML insights at lightning speed with zero-config observability for model drift, performance, and data quality. Phoenix is an Open Source ML Observability library designed for the Notebook. The toolset is designed to ingest model inference data for LLMs, CV, NLP and tabular datasets. It allows Data Scientists to quickly visualize their model data, monitor performance, track down issues & insights, and easily export to improve. Deep Learning Models (CV, LLM, and Generative... -
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Cleanlab
The standard data-centric AI package for data quality and ML
cleanlab helps you clean data and labels by automatically detecting issues in a ML dataset. To facilitate machine learning with messy, real-world data, this data-centric AI package uses your existing models to estimate dataset problems that can be fixed to train even better models. cleanlab cleans your data's labels via state-of-the-art confident learning algorithms, published in this paper and blog. See some of the datasets cleaned with cleanlab at labelerrors.com. This package helps you... -
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AutoGluon
AutoGluon: AutoML for Image, Text, and Tabular Data
... selection/ensembling, architecture search, and data processing. Easily improve/tune your bespoke models and data pipelines, or customize AutoGluon for your use-case. AutoGluon is modularized into sub-modules specialized for tabular, text, or image data. You can reduce the number of dependencies required by solely installing a specific sub-module via: python3 -m pip install <submodule>. -
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OpticSim.jl
Optical Simulation software
OpticSim.jl is a Julia package for geometric optics (ray tracing) simulation and optimization of complex optical systems developed by the Microsoft Research Interactive Media Group and the Microsoft Hardware Architecture Incubation Team (HART). It is designed to allow optical engineers to create optical systems procedurally and then to simulate and optimize them. Unlike Zemax, Code V, or other interactive optical design systems OpticSim.jl has limited support for interactivity, primarily in... -
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Learn Julia the Hard Way
Learn Julia the hard way
... be hard-pressed to find tasks it's completely unsuitable for (although that does not mean it's the best or easiest choice for any of them). Julia was developed with the occasional reference to R, and with an avowed intent to improve upon R's clunkiness. R is a great language, but relatively slow, to the point that most people use it to rapidly prototype, and then implement the algorithm for production in Python or Java. Julia seeks to be as approachable as R but without the speed penalty. -
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Davinci
Davinci is a DVsaaS (Data Visualization as a Service) Platform
... intelligence, etc. Sharing and intelligence capability means users could share their dashboards with others, which stimulates them to improve the visualization ability both in aesthetic perception and technical skills. In the field of data visualization, Davinci attaches great importance to basic interaction ability and various chart options; meanwhile, it lays more stress on integration and customization capability as well as sharing and intelligence capability. -
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Data Science at the Command Line
Data science at the command line
...-line tools to quickly obtain, scrub, explore, and model your data. To get you started, author Jeroen Janssens provides a Docker image packed with over 100 Unix power tools, useful whether you work with Windows, macOS, or Linux. You’ll quickly discover why the command line is an agile, scalable, and extensible technology. Even if you’re comfortable processing data with Python or R, you’ll learn how to greatly improve your data science workflow by leveraging the command line’s power. -
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Vaex
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python
Data science solutions, insights, dashboards, machine learning, deployment. We start at 100GB. Vaex is a high-performance Python library for lazy Out-of-Core data frames (similar to Pandas), to visualize and explore big tabular datasets. It calculates statistics such as mean, sum, count, standard deviation etc, on an N-dimensional grid for more than a billion (10^9) samples/rows per second. Visualization is done using histograms, density plots and 3d volume rendering, allowing interactive... -
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Penthode
Penthode simulates, draw and plot electrical power distributions
Given a simple net-list describing the high level power architecture of your system Penthode: - simulates the voltage and current from device turn on to the steady state. - highlights components working out of specification - draws a nice power tree diagram showing the currents/powers balance - plots node transient voltage and gate current waveforms It is possible to change component parameters interactively to improve the design -
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Yggdrasill
3D Evolutionary Tree Visualization
..., an extinct species overlay and more. Later updates will include the full ToL dataset, improve tree generation and overall accessability, as well as adding access to other datasets. Special thanks go to the Tree of Life Web Project and all its contributors for providing the data and to Unity Technologies for free access to Unity 5. -
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iOVFDT
iOVFDT algorithm of incremental decision tree
... incrementally optimized very fast decision tree (iOVFDT). Inheriting the use of Hoeffding bound in VFDT algorithm for node-splitting check, it contains four optional strategies of functional tree leaf, which improve the classifying accuracy. In addition, a multi-objective incremental optimization mechanism investigates a balance among accuracy, mode size and learning speed... -
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jFox Journal
Trading journal for Currency,Stock,Commodity traders
jFox Trading Journal is software developed mainly for currency traders,it provides advanced data analysis to improve traders ability to reach higher profits and eliminate losses.jFox keeps your data in one place.To access or modify any of your data jFox provide simple user friendly GUI.By generating graphs and statistics automaticly,user only needs to provide his data to have full overview over his trades and trading performance. -
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AsphaltOpen is a project to visualize data collected during road asphalting operations. Asphalt contractors can use the software to visualize their operations, learn from the visualizations, and improve their processes continually.