Search Results for "data" - Page 19
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Showing 3123 open source projects for "data"
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99.99% Uptime for MySQL and PostgreSQL on Google CloudCloud SQL Enterprise Plus gives you a 99.99% availability SLA with near-zero downtime maintenance—typically under 10 seconds. Get 2x better read/write performance, intelligent data caching, and 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server with built-in vector search for gen AI apps. New customers get $300 in free credit.
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Granite TSFM
Foundation Models for Time Series
granite-tsfm collects public notebooks, utilities, and serving components for IBM’s Time Series Foundation Models (TSFM), giving practitioners a practical path from data prep to inference for forecasting and anomaly-detection use cases. The repository focuses on end-to-end workflows: loading data, building datasets, fine-tuning forecasters, running evaluations, and serving models. It documents the currently supported Python versions and points users to where the core TSFM models are hosted and how to wire up service components. ... -
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Tarsier
Vision utilities for web interaction agents
At Reworkd, we iterated on all these problems across tens of thousands of real web tasks to build a powerful perception system for web agents... Tarsier! In the video below, we use Tarsier to provide webpage perception for a minimalistic GPT-4 LangChain web agent. Tarsier visually tags interactable elements on a page via brackets + an ID e.g. [23]. In doing this, we provide a mapping between elements and IDs for an LLM to take actions upon (e.g. CLICK [23]). We define interactable elements... -
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srsly
Modern high-performance serialization utilities for Python
This package bundles some of the best Python serialization libraries into one standalone package, with a high-level API that makes it easy to write code that's correct across platforms and Pythons. This allows us to provide all the serialization utilities we need in a single binary wheel. Currently supports JSON, JSONL, MessagePack, Pickle, and YAML. Serialization is hard, especially across Python versions and multiple platforms. After dealing with many subtle bugs over the years (encodings,... -
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Avalanche
End-to-End Library for Continual Learning based on PyTorch
Avalanche is an end-to-end Continual Learning library based on Pytorch, born within ContinualAI with the unique goal of providing a shared and collaborative open-source (MIT licensed) codebase for fast prototyping, training and reproducible evaluation of continual learning algorithms. Avalanche can help Continual Learning researchers in several ways. This module maintains a uniform API for data handling: mostly generating a stream of data from one or more datasets. It contains all the major CL benchmarks (similar to what has been done for torchvision). Provides all the necessary utilities concerning model training. This includes simple and efficient ways of implementing new continual learning strategies as well as a set of pre-implemented CL baselines and state-of-the-art algorithms you will be able to use for comparison! ... -
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DeepLabCut
Implementation of DeepLabCut
DeepLabCut™ is an efficient method for 2D and 3D markerless pose estimation based on transfer learning with deep neural networks that achieves excellent results (i.e. you can match human labeling accuracy) with minimal training data (typically 50-200 frames). We demonstrate the versatility of this framework by tracking various body parts in multiple species across a broad collection of behaviors. The package is open source, fast, robust, and can be used to compute 3D pose estimates or for multi-animals. Please see the original paper and the latest work below! ... -
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HTTPie
A CLI, cURL-like tool for humans
HTTPie is a modern command-line HTTP client that makes CLI interaction with web services as human-friendly as possible. It offers a plethora of friendly features that make it an excellent curl alternative. It is equipped with an intuitive UI, JSON support, syntax highlighting and so much more. HTTPie gives a single http command for sending arbitrary HTTP requests with a simple, natural syntax, and displayed in a formatted, colorized terminal output. HTTPie can be installed on macOS,... -
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SleepFM-Clinical
Improve human sleep through scientifically
...The clinical release includes additional features for controlled experimentation, such as logging capabilities, adjustable parameter sets, and protocols suitable for sleep studies and therapeutic settings. It also integrates tools for clinicians to configure sessions, annotate events, and potentially link with biofeedback data, enabling a more nuanced understanding of sound’s effect on sleep architecture over time. -
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plexe
Build a machine learning model from a prompt
plexe lets you build machine-learning systems from natural-language prompts, turning plain English goals into working pipelines. You describe what you want—a predictor, a classifier, a forecaster—and the tool plans data ingestion, feature preparation, model training, and evaluation automatically. Under the hood an agent executes the plan step by step, surfacing intermediate results and artifacts so you can inspect or override choices. It aims to be production-minded: models can be exported, versioned, and deployed, with reports to explain performance and limitations. ... -
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Core ML Tools
Core ML tools contain supporting tools for Core ML model conversion
...Core ML is an Apple framework to integrate machine learning models into your app. Core ML provides a unified representation for all models. Your app uses Core ML APIs and user data to make predictions, and to fine-tune models, all on the user’s device. Core ML optimizes on-device performance by leveraging the CPU, GPU, and Neural Engine while minimizing its memory footprint and power consumption. Running a model strictly on the user’s device removes any need for a network connection, which helps keep the user’s data private and your app responsive. -
Easily Host LLMs and Web Apps on Cloud RunRun frontend and backend services, batch jobs, host LLMs, and queue processing workloads without the need to manage infrastructure. Cloud Run gives you on-demand GPU access for hosting LLMs and running real-time AI—with 5-second cold starts and automatic scale-to-zero so you only pay for actual usage. New customers get $300 in free credit to start.
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Goose Developer Agent
Goose is a developer agent that operates from your command line
...Guided by you, it can intelligently assess your project's needs, generate the required code or modifications, and implement these changes on its own. Goose can interact with a multitude of tools via external APIs such as Jira, GitHub, Slack, infrastructure and data pipelines, and more -- if your task uses a shell command or can be carried out by a Python script, Goose can do it for you too! Like semi-autonomous driving, Goose handles the heavy lifting, allowing you to focus on other priorities. Simply set it on a task and return later to find it completed, boosting your productivity with less manual effort. -
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Crawl4AI
Open-source LLM Friendly Web Crawler & Scraper
Crawl4AI is a high-performance, AI‑ready web crawler tailored for LLM data ingestion and RAG pipelines. It supports adaptive crawling heuristics (stopping when enough info is gathered), structured markdown output, and high-speed parallel execution. Designed to operate at scale with optional Docker deployment and framework integrations. -
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Vanna
Chat with your SQL database
Vanna.AI is an AI-powered tool for natural language database querying, enabling users to interact with databases using simple English queries. It converts natural language questions into SQL queries, making data access more intuitive for non-technical users. -
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SetFit
Efficient few-shot learning with Sentence Transformers
SetFit is an efficient and prompt-free framework for few-shot fine-tuning of Sentence Transformers. It achieves high accuracy with little labeled data - for instance, with only 8 labeled examples per class on the Customer Reviews sentiment dataset, SetFit is competitive with fine-tuning RoBERTa Large on the full training set of 3k examples. -
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MegaParse
File Parser optimised for LLM Ingestion with no loss
...It efficiently parses various document formats, such as PDFs, DOCX, and PPTX, converting them into formats ideal for processing by LLMs. This tool is essential for applications that require accurate and comprehensive data extraction from diverse document types. -
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Restaurant Management System
Restaurant Management System written in Python using Tkinter
...Storing the restaurant configuration: configure facility name, table/seat counts, and menu with the ability to modify them in the future. Users will have the ability to modify the data through the “Configure Facility/Menu” section of the app. Create bills for the chef (backend): The application will first send the order to the kitchen for cooks to see, prepare, and fulfill the order. -
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ModernGL
Modern OpenGL binding for Python
...It provides an intuitive API for rendering 2D and 3D graphics, making it accessible to both beginners and experienced developers. ModernGL is suitable for applications such as games, simulations, and data visualizations. -
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Nixtla TimeGPT
TimeGPT-1: production ready pre-trained Time Series Foundation Model
TimeGPT is a production ready, generative pretrained transformer for time series. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code. Whether you're a bank forecasting market trends or a startup predicting product demand, TimeGPT democratizes access to cutting-edge predictive insights, eliminating the need for a dedicated team of machine learning engineers. A generative model for time series. TimeGPT is capable of... -
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Watchman
A file watching service that records when files change
Watchman purpose is to watch files and record when there are changes. It can trigger actions (rebuilding assets, for example) when there is a change in matching files. The watchman executable has both the client and the server components of the watchman service. When running watchman, it will attempt to communicate with your existing server instance (each user has their own persistent process), and will attempt to start it if it doesn’t exist. There are some options that affect how watchman... -
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verl
Volcano Engine Reinforcement Learning for LLMs
Data pipelines treat human feedback, simulated environments, and synthetic preferences as interchangeable sources, which helps with rapid experimentation. VERL is meant for both research and production hardening: logging, checkpointing, and evaluation suites are built in so you can track learning dynamics and regressions over time. -
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Google DeepMind GraphCast and GenCast
Global weather forecasting model using graph neural networks and JAX
...GraphCast is designed to perform high-resolution atmospheric simulations using the ERA5 dataset from ECMWF, while GenCast extends the approach with diffusion-based ensemble forecasting for probabilistic weather prediction. Both models are built on JAX and integrate advanced neural architectures capable of learning from multi-scale geophysical data represented on icosahedral meshes. The package includes pretrained model weights, normalization statistics, and demonstration notebooks that allow users to replicate and fine-tune weather forecasting experiments in Colab or on Google Cloud TPUs and GPUs. -
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Large Concept Model
Language modeling in a sentence representation space
...It organizes training around concepts (rather than just raw labels), encouraging models to understand attributes, relations, and compositional structure that transfer across tasks. The repository provides training loops, data tooling, and evaluation routines to learn and probe these concept embeddings, typically from large image–text or weakly supervised corpora. It includes utilities to build concept vocabularies, map supervision signals to those vocabularies, and measure zero-shot or few-shot generalization. Probing tools help diagnose what the model knows—e.g., attribute recognition, relation understanding, or compositionality—so you can iterate on data and objectives. ... -
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Letterboxd Recommendations
Scraping publicly-accessible Letterboxd data for movie recommendations
Scraping publicly-accessible Letterboxd data and creating a movie recommendation model with it that can generate recommendations when provided with a Letterboxd username. A user's "star" ratings are scraped from their Letterboxd profile and assigned numerical ratings from 1 to 10 (accounting for half stars). Their ratings are then combined with a sample of ratings from the top 4000 most active users on the site to create a collaborative filtering recommender model using singular value decomposition (SVD). ... -
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PaddleNLP
Easy-to-use and powerful NLP library with Awesome model zoo
PaddleNLP It is a natural language processing development library for flying paddles, with Easy-to-use text area API, Examples of applications for multiple scenarios, and High-performance distributed training Three major features, aimed at improving the modeling efficiency of the flying oar developer's text field, aiming to improve the developer's development efficiency in the text field, and provide rich examples of NLP applications. Provide rich industry-level pre-task capabilities Taskflow And process-wide text area API: Support for the loading of rich Chinese data sets Dataset API, can flexibly and efficiently complete data pretreatment Data API, Preset 60 + pre-training word vector Embedding API, Providing 100 + pre-training model Transformer API Wait, the efficiency of NLP task modeling can be greatly improved. -
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Pelican
Static site generator that supports Markdown and reST syntax
Pelican is a static site generator that requires no database or server-side logic. Chronological content (e.g., articles, blog posts) as well as static pages. Integration with external services. Site themes (created using Jinja2 templates). Publication of articles in multiple languages. Generation of Atom and RSS feeds. Code syntax highlighting via Pygments. Import existing content from WordPress, Dotclear, or RSS feeds. Fast rebuild times due to content caching and selective output writing.... -
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LLMs-from-scratch
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
...The focus is on readability, correctness, and experimentation, making it ideal for students and practitioners transitioning from theory to working systems. By the end, you have a grounded sense of how data pipelines, optimization, and inference interact to produce fluent text.
