Search Results for "dataset"
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Showing 55 open source projects for "dataset"
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1
Passport Index Dataset
Passport Index 2023: visa requirements for 199 countries, in .csv
There are 6 datasets with identical visa requirements data. Three datasets are matrix and three are long (tidy) formats. Each comes in 3 versions: with country codes as specified in ISO-2 (two-letter codes), ISO-3 (three-letter codes), and full country names from no particular standard. In distance matrices (files with matrix in the filename), the first column represents a passport (=from), each remaining column represents a destination (=to). Files in tidy format (with tidy in filename)... -
2
GH Archive
GH Archive is a project to record the public GitHub timeline
...The dataset is also published through Google BigQuery for large-scale SQL-style exploration without downloading every archive. Its structure supports trend analysis, visualizations, machine learning, and open-source ecosystem research. The repository contains the crawler, supporting scripts, and website code, while the actual event files are hosted separately. -
3
NYC Taxi Data
Import public NYC taxi and for-hire vehicle (Uber, Lyft)
...It also contains example analyses—spatial and temporal visualizations like maps, time-series plots, and hotspot detection—highlighting insights such as patterns of demand, peak times, and geospatial distributions. The repository is often used as a benchmark dataset and example for teaching, benchmarking, and demonstration purposes in the data science and urban analytics communities. -
4
all AI news
A list of online news & info sources in the AI/ML/Data Science space
...Overall, it provides a foundational dataset for tracking AI industry trends and updates. -
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5
Marble Skill Taxonomy
Structured taxonomy of what children learn across the primary years
Marble Skill Taxonomy is an open structured dataset that maps what children learn across primary and elementary education. It breaks curriculum content into fine-grained micro-topics instead of leaving learning goals as broad standards. Each topic includes subject, domain, age range, description, evidence criteria, assessment prompt, and stable identifiers. The dataset also defines prerequisite relationships, so developers can trace what a learner should master before a concept. ... -
6
emojilib
Emoji keyword library
Emoji keyword library. Make emoji searchable with this keyword library. If you are looking for the unicode emoji dataset, including version, grouping, ordering, and skin tone support flag, check out unicode-emoji-json. -
7
BIMserver
The open source BIMserver platform
...The main advantage of this approach is the ability to query, merge and filter the BIM model and generate IFC output (i.e. files) on the fly. Thanks to its multi-user support, multiple people can work on their own part of the dataset, while the complete dataset is updated on the fly. Other users can get notifications when the model (or a part of it) is updated. -
8
React Chart.js
React components for Chart.js, the most popular charting library
...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 and bars to merge together. This is because to track changes in the dataset series, the library needs a key to be specified. If none is found, it can't tell the difference between the datasets while updating. Specify a different property to be used as a key by passing a datasetIdKey prop to your chart component. -
9
SponsorBlock
Skip YouTube video sponsors (browser extension)
SponsorBlock is an open-source crowdsourced browser extension and open API for skipping sponsor segments in YouTube videos. Users submit when a sponsor happens from the extension, and the extension automatically skips sponsors it knows about using a privacy-preserving query system. It also supports skipping other categories, such as intros, outros, and reminders to subscribe, and skipping to the point with highlights. The extension also features an upvote/downvote system with a weighted... -
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10
Petastorm
Petastorm library enables single machine or distributed training
...This library enables single machine or distributed training and evaluation of deep learning models directly from datasets in Apache Parquet format. Petastorm supports popular Python-based machine learning (ML) frameworks such as Tensorflow, PyTorch, and PySpark. It can also be used from pure Python code. A dataset created using Petastorm is stored in Apache Parquet format. On top of a Parquet schema, petastorm also stores higher-level schema information that makes multidimensional arrays into a native part of a petastorm dataset. Petastorm supports extensible data codecs. These enable a user to use one of the standard data compressions (jpeg, png) or implement her own. -
11
v2ray-rules-dat
V2Ray routing rules file enhanced version, which can replace V2Ray
v2ray-rules-dat is a repository that compiles and distributes enhanced rule data (domain lists, geo-IP/geo-domain data, block/proxy/detect lists) intended for use with tools like V2Ray, Xray-core, and similar network/proxy frameworks. The dataset serves as an alternative or supplement to official geoip/ geosite data files, often providing more up-to-date, community-curated entries — enabling better routing, blocking, or traffic management when using those proxy tools. The repository is regularly updated (weekly sync upstream) and provides releases containing comprehensive data files (e.g. geoip.dat, geosite.dat, plus multiple .txt rule lists) plus checksums for integrity verification. ... -
12
Karpathy-Inspired Claude Code Guidelines
A single CLAUDE.md file to improve Claude Code behavior
Karpathy-Inspired Claude Code Guidelines is a curated learning and experimentation repository inspired by the work and teaching philosophy of Andrej Karpathy, designed to help learners build practical competence in deep learning, neural networks, and AI infrastructure. The project organizes a progressive path through exercises, notebooks, code examples, and practical mini-projects that echo Karpathy’s approach to “learning by doing,” where students build core concepts from first principles... -
13
Recursive Language Models
General plug-and-play inference library for Recursive Language Models
...It provides a consistent API that abstracts away many of the repetitive engineering patterns in RL research and application work, letting developers focus on modeling, experimentation, and fine-tuning rather than infrastructure plumbing. Within the framework, you can define custom agents, environments, policy networks, and reward structures while leveraging built-in dataset utilities, logging, and checkpointing for reproducible experiments. RLM also includes integration with popular simulation environments and benchmark suites, giving researchers a ready-made playground for algorithm comparison and performance tracking. -
14
User Agents
A JavaScript library for generating random user agents with data
...Unlike simpler random user agent generators, it uses frequency-weighted datasets to ensure that generated values reflect how browsers are actually used in the wild. The dataset is updated automatically on a daily basis, ensuring that generated user agents remain current and relevant over time. In addition to user agent strings, the library can produce detailed browser fingerprint data such as screen size, platform, connection type, and device category. It also includes flexible filtering capabilities that allow developers to generate user agents matching specific criteria such as device type, operating system, or browser version. -
15
kagglehub
Python library to access Kaggle resources
kagglehub is a Python library for accessing Kaggle resources directly from Python code. It provides a simple API for downloading datasets, models, competition files, and notebook outputs without requiring users to manually manage every URL or file path. The library is designed to work both inside and outside Kaggle Notebooks, with native behavior that can adapt when it runs in Kaggle’s hosted notebook environment. It is useful for machine learning workflows where data, models, and notebook... -
16
LLM Datasets
Curated list of datasets and tools for post-training
...Quality is a recurring theme: examples and utilities help filter low-value samples, enforce length limits, and split train/validation consistently so results are comparable. Licensing and provenance are surfaced to encourage compliant usage and to guide dataset selection in commercial settings. For practitioners, the repo is a practical “starting pantry” that accelerates experimentation and helps keep data wrangling from dominating the project timeline. -
17
ARC-AGI
The Abstraction and Reasoning Corpus
...The dataset is structured as grid-based puzzles, where each task requires understanding transformations such as symmetry, counting, or spatial manipulation. Unlike traditional machine learning benchmarks, ARC emphasizes generalization and reasoning over statistical pattern recognition, making it particularly challenging for current AI systems. -
18
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... -
19
YOLOV4 Pytorch
This is a source code for YoloV4-pytorch that can be used to train you
YOLOV4 Pytorch is a PyTorch implementation of the YOLOv4 object detection model for training and running custom detection systems. The repository is structured around practical workflows, including training, prediction, evaluation, anchor generation, model configuration, and dataset annotation utilities. It supports VOC-style datasets and includes scripts for prediction, mAP evaluation, FPS testing, video prediction, batch prediction, and heatmap generation. The project added multi-GPU training, seed settings for reproducible results, adaptive learning rate behavior based on batch size, and both step and cosine learning rate schedules. ... -
20
YOLOV3 Pytorch
This is a source code for yolo3-pytorch
YOLOV3 Pytorch is a PyTorch implementation of the YOLOv3 object detection model built for training, prediction, and evaluation. The repository provides a complete workflow for users who want to train their own object detector with VOC-style data or use pretrained weights. It includes utilities for annotation conversion, anchor generation, image prediction, video prediction, batch prediction, FPS measurement, heatmap output, and mAP evaluation. The project added multi-GPU training, target... -
21
Augmentor.jl
A fast image augmentation library in Julia for machine learning
A fast library for increasing the number of training images by applying various transformations. Augmentor is a real-time image augmentation library designed to render the process of artificial dataset enlargement more convenient, less error prone, and easier to reproduce. It offers the user the ability to build a stochastic image-processing pipeline (or simply augmentation pipeline) using image operations as building blocks. In other words, an augmentation pipeline is little more but a sequence of operations for which the parameters can (but need not) be random variables, as the following code snippet demonstrates. -
22
Unet
Source code for unet-pytorch, which can train its own model
...The repository is built around training, prediction, and mIoU evaluation for VOC-style segmentation data and medical-style datasets. It includes scripts for general training, medical dataset training, prediction, annotation handling, model summaries, and evaluation. The project supports multiple backbones, data processing utilities, extensive comments, and adjustable training parameters. Its README notes that U-Net is better suited to datasets with fewer features and shallow visual structures, such as medical image segmentation, rather than complex VOC-style scenes. ... -
23
DeepLabv3 Plus
Encoder-Decoder with Atrous Separable Convolution
...It implements the encoder-decoder architecture with atrous separable convolution and provides a practical workflow for training, prediction, and mIoU evaluation. The repository supports VOC-style segmentation datasets and includes utilities for annotation generation, JSON dataset conversion, model summary inspection, prediction, and metric calculation. It provides pretrained weight workflows for MobileNetV2 and Xception backbones and notes that the correct backbone should be selected during training and prediction. The project also supports multi-GPU training, multiple backbones, learning rate schedules with step and cosine options, optimizer selection, and adaptive learning rate behavior based on batch size. ... -
24
Faster-Rcnn
This is a pytorch implementation library of faster-rcnn
Faster-Rcnn is a PyTorch implementation of the Faster R-CNN two-stage object detection model. It is designed for training and evaluating detectors on VOC-format datasets, including VOC07+12 and custom datasets arranged with VOC-style annotations and images. The repository includes scripts for training, prediction, evaluation, annotation generation, and model summary inspection. It supports backbone options through pretrained VGG and ResNet weights, making it useful for comparing feature... -
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SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
...Separate models are trained for different speaker counts, and the largest-capacity model dynamically determines the actual number of speakers in a mixture. The repository includes all necessary scripts for training, dataset preparation, distributed training, evaluation, and audio separation.