Search Results for "data quality cleansing" - Page 14
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Showing 909 open source projects for "data quality cleansing"
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Crane
Crane is a FinOps Platform for Cloud Resource Analytics and Economics
Crane is a FinOps Platform for Cloud Resource Analytics and Economics in Kubernetes clusters. The goal is not only to help users to manage cloud cost easily but also to ensure the quality of applications. -
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CausalNex
A Python library that helps data scientists to infer causation
CausalNex is a Python library that uses Bayesian Networks to combine machine learning and domain expertise for causal reasoning. You can use CausalNex to uncover structural relationships in your data, learn complex distributions, and observe the effect of potential interventions. -
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pseudocode.js
Beautiful pseudocode for the Web
pseudocode.js is a JavaScript library that typesets pseudocode beautifully to HTML. Pseudocode.js takes a LaTeX-style input that supports the algorithmic constructs from LaTeX's algorithm packages. With or without LaTeX experience, a user should find the grammar fairly intuitive. The HTML output produced by pseudocode.js is (almost) identical to the pretty algorithms printed on publications that are typeset by LaTeX. Inserting math formulas in pseudocode.js is as easy as LaTeX. Just enclose... -
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Swiple
Swiple enables you to easily observe, understand, validate data
...Seamlessly incorporate data quality checks into your existing workflows without any coding or infrastructure changes, allowing you to focus on what matters most - your data. Save engineers weeks of time generating data quality checks. Swiple analyzes your dataset and builds data quality checks based on what is observed in your data. You just pick the ones you want. -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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fastMRI
A large open dataset + tools to speed up MRI scans using ML
fastMRI is a large-scale collaborative research project by Facebook AI Research (FAIR) and NYU Langone Health that explores how deep learning can accelerate magnetic resonance imaging (MRI) acquisition without compromising image quality. By enabling reconstruction of high-fidelity MR images from significantly fewer measurements, fastMRI aims to make MRI scanning faster, cheaper, and more accessible in clinical settings. The repository provides an open-source PyTorch framework with data loaders, subsampling utilities, reconstruction models, and evaluation metrics, supporting both research reproducibility and practical experimentation. ... -
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DataGym.ai
Open source annotation and labeling tool for image and video assets
DATAGYM enables data scientists and machine learning experts to label images up to 10x faster. AI-assisted annotation tools reduce manual labeling effort, give you more time to finetune ML models and speed up your go to market of new products. Accelerate your computer vision projects by cutting down data preparation time up to 50%. A machine learning model is only as good as its training data. DATAGYM is an end-to-end workbench to create, annotate, manage, and export the right training data... -
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Amplify
Automatic enrichment, enhancement, and explanation of your data
Amplify attaches afterburners to your data. Amplify explains metadata extraction, classification, tagging, and reporting. Eriches derivative data generation like thumbnails, previews, conversions, etc. Enhances batteries-included value-adds like data quality reports, image augmentation, OCR, translations, etc. Amplify leverages the decentralized compute provided by Bacalhau to magically enrich your data. -
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PRM800K
800,000 step-level correctness labels on LLM solutions to MATH problem
...The repository releases the raw labels and the labeler instructions used in two project phases, enabling researchers to study how human raters graded intermediate reasoning. Data are stored as newline-delimited JSONL files tracked with Git LFS, where each line is a full solution sample that can contain many step-level labels and rich metadata such as labeler UUIDs, timestamps, generation identifiers, and quality-control flags. Each labeled step can include multiple candidate completions with ratings of -1, 0, or +1, optional human-written corrections (phase 1), and a chosen completion index, along with a final finish reason such as found_error, solution, bad_problem, or give_up. -
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linSmith
Smith chart intended for educational use
A Smith charting program. You can enter either discrete components or transmission lines, see the results on screen and/or generate Postscript output. Component values can be changed numerically or using scrollbars. -
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TransMCL
a noval Transcriptome optimization tool
To improve the quality of transcriptome assembly, we introduce TransMCL, a novel transcriptome optimization tool, to reconstruct full-length coding sequences while eliminating redundancy from assembled transcriptomes. TransMCL employs homologs from closely related species to guide the assembly, clustering raw transcripts from transcriptome data and genes from annotated genomes into hierarchical ortholog groups (HOGs). -
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SASUnit
Unit testing for SAS(TM)-programs
SASUnit is a unit testing framework for SAS(TM)-programs. It can be used for the development, execution and automatic documentation of tests for SAS programs. SASUnit is written purely on the basis of SAS macros and a few shell commands. There are two videos on YouTube: * Getting started: https://www.youtube.com/watch?v=Kc66hADHNyI * Usage of setup scripts: https://www.youtube.com/watch?v=9drW_6eg6G4 SASUnit is brought to you by HMS Analytical Software... -
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Feathr
A scalable, unified data and AI engineering platform for enterprise
Feathr is a data and AI engineering platform that is widely used in production at LinkedIn for many years and was open sourced in 2022. It is currently a project under LF AI & Data Foundation. Define data and feature transformations based on raw data sources (batch and streaming) using Pythonic APIs. Register transformations by names and get transformed data(features) for various use cases including AI modeling, compliance, go-to-market and more. Share transformations and data(features)... -
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VALL-E
PyTorch implementation of VALL-E (Zero-Shot Text-To-Speech)
...Specifically, we train a neural codec language model (called VALL-E) using discrete codes derived from an off-the-shelf neural audio codec model, and regard TTS as a conditional language modeling task rather than continuous signal regression as in previous work. During the pre-training stage, we scale up the TTS training data to 60K hours of English speech which is hundreds of times larger than existing systems. VALL-E emerges in-context learning capabilities and can be used to synthesize high-quality personalized speech with only a 3-second enrolled recording of an unseen speaker as an acoustic prompt. Experiment results show that VALL-E significantly outperforms the state-of-the-art zero-shot TTS system in terms of speech naturalness and speaker similarity. ... -
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Aestel
Applications for data management
"Information is data in action", and, consequently, having good quality data is essential. The AESTEL package contains two highly configurable applications for data management: A data loader and a reporting application, i.e. DataLoader and AEREA, respectively. The data loader application applies user-defined instructions to validate, process and load data. -
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UDPspeeder
A Tunnel which Improves your Network Quality
UDPspeeder is a tunneling utility focused on improving UDP traffic quality over high-latency, unstable, or packet-loss-prone links. Its core technique is Forward Error Correction, which sends redundant data so the connection can recover from packet loss without waiting for retransmission. Used by itself, it improves UDP-based connections, but it can also be paired with UDP-based VPN tools to support broader traffic types through the VPN layer. -
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Self-learning-Computer-Science
Resources to learn computer science in your spare time
Self-learning Computer Science is a curated, open-source guide repository designed to help learners independently study computer science topics using high-quality university-level resources. The author (an undergraduate CS student) assembled links to courses from institutions like MIT, UC Berkeley, Stanford, etc., covering mathematics, programming, data structures/algorithms, computer architecture, machine learning, software engineering and more. It’s aimed at learners who find traditional course structures restrictive and want a flexible, self-paced path through CS, with a focus on building depth and breadth rather than shortcut exam skills. ... -
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Rachota
Easy-to-use personal time tracking application for Windows and Unix
Rachota is a portable application for time-tracking your work on different projects. It runs on Windows, Linux, Solaris and Mac. Rachota displays time data in diagram form, creates customized reports or invoices and provides suggestions to increase your efficiency. -
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Data science blogs
A curated list of data science blogs
Data Science Blogs is a curated repository that aggregates a wide range of high-quality blogs and resources related to data science, machine learning, and analytics into a single organized collection. It serves as a discovery platform for practitioners, researchers, and learners who want to stay updated with industry trends, techniques, and insights without manually searching for reliable sources. -
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Lyra
A Very Low-Bitrate Codec for Speech Compression
...It replaces hand-engineered codecs with learned models that capture speech characteristics more efficiently and reconstruct waveforms with a neural vocoder. The system targets mobile-class hardware, balancing latency and quality so it can run in real-time on phones. Its architecture is resilient to packet loss and jitter through framing strategies and error concealment, helping conversations remain understandable under adverse conditions. The codebase includes encoder and decoder components, along with tools for data preparation and evaluation. By pushing bitrates down to just a few kilobits per second while retaining quality, lyra expands access to voice calls where bandwidth is scarce. -
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GitHub Rater
Check your GitHub rating, view results and enhance your quality
...The application’s frontend is built with modern web frameworks and interacts with GitHub’s API to gather real-time data, handling errors and edge cases gracefully. Its interface visualizes metrics and recommendations, making the assessment accessible even to those unfamiliar with raw GitHub statistics. -
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SQLBucket
Lightweight library to write, orchestrate and test your SQL ETL
SQLBucket is a lightweight framework to help write, orchestrate and validate SQL data pipelines. It gives the possibility to set variables and introduces some control flow using the fantastic Jinja2 library. It also implements a very simplistic unit and integration test framework where you can validate the results of your ETL in the form of SQL checks. With SQLBucket, you can apply TDD principles when writing data pipelines. To start working, you need to instantiate your SQLBucket core... -
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Super-PDF-Editor
World's most comprehensive, powerful, process-based PDF editor
...OCR performs in pdf files, scanned pdf files and any pdf files. OCR performs in image files, and supports multiple image formats. Auto and manual image enhancement for better OCR accuracy and quality. Supports 165+ languages with three languages data set. Use Multiple Languages at once. International Languages: 127 Languages, High, Medium, and Fast Quality. Scanned Images (jpg, png, gif, tiff, bmp) Multi-Page and TIFF and GIF, Scanned PDFs. -
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ASH Viewer provides a graphical view of active session history data within the Oracle and PostgreSQL DB
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Data Science Collected Resources
Carefully curated resource links for data science in one place
...Its goal is to provide learners and practitioners with easy access to high-quality resources related to data science tools, programming languages, cloud platforms, and machine learning techniques. The repository includes links to materials discussing topics such as artificial intelligence research, AWS infrastructure, machine learning algorithms, and data analysis tools. It also contains supplementary documents like cheat sheets and machine learning notes that help readers review important concepts quickly. -
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EnCodec
State-of-the-art deep learning based audio codec
...Unlike traditional codecs (like MP3 or Opus), Encodec uses a learned quantizer and decoder to reconstruct complex waveforms with remarkable accuracy at bitrates as low as 1.5 kbps. It employs a convolutional encoder–decoder architecture trained with perceptual loss functions that optimize for human auditory quality rather than raw waveform distance. The model can operate in real time and supports variable bandwidths, bitrates, and multi-band audio. Encodec has applications in speech and music compression, generative modeling, and efficient data transmission for communication systems. The repository includes pretrained checkpoints, PyTorch inference code, and examples for integrating Encodec as a module in downstream generative or streaming systems.
