Search Results for "data entry"
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Showing 17 open source projects for "data entry"
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AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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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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OpenDAN
OpenDAN is an open source Personal AI OS
OpenDAN is an open-source Personal AI OS , that consolidates various AI modules in one place for your personal use. The goal of OpenDAN (Open and Do Anything Now with AI) is to create a Personal AI OS , which provides a runtime environment for various Al modules as well as protocols for interoperability between them. With OpenDAN, users can securely collaborate with various AI modules using their private data to create powerful personal AI agents, such as butlers, lawyers, doctors, teachers,... -
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paperless-gpt
Use LLMs and LLM Vision (OCR) to handle paperless-ngx
...The platform is particularly useful for individuals and organizations managing large volumes of paperwork, such as invoices, contracts, or records, as it reduces the need for manual data entry. -
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Kaggle Solutions
Collection of Kaggle Solutions and Ideas
Kaggle Solutions is an open-source repository that compiles winning solutions, insights, and educational resources from hundreds of Kaggle data science competitions. The repository acts as a knowledge base for competitive machine learning by collecting solution write-ups, discussion threads, code notebooks, and tutorial resources shared by top Kaggle participants. Each competition entry typically includes information about the dataset, evaluation metrics, modeling strategies, and techniques used by high-ranking competitors. ... -
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Nexent
Zero-code platform for building AI agents from natural language input
Nexent is an open source platform designed to enable users to create intelligent agents using natural language instead of traditional programming or visual orchestration tools. It focuses on a zero-code approach, allowing users to define workflows and agent behavior purely through language prompts, significantly lowering the barrier to entry for AI development. Built on the MCP ecosystem, Nexent integrates a wide range of tools, models, and data sources into a unified environment for agent creation and execution. Nexent supports multi-agent collaboration, enabling multiple intelligent agents to interact and coordinate tasks within complex workflows. It also includes capabilities for data processing, knowledge tracing, and multimodal interaction, allowing agents to work with different input and output formats. ... -
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LLMFarm
llama and other large language models on iOS and MacOS offline
LLMFarm is a framework designed to simplify the deployment, management, and utilization of large language models in local or self-hosted environments, focusing on accessibility and efficient resource usage. It enables users to run LLMs on personal hardware or private infrastructure, reducing dependency on external APIs and improving data privacy. The system typically provides a user-friendly interface for loading models, configuring inference parameters, and interacting with them through chat or task-based workflows. It emphasizes modularity, allowing users to integrate different models, backends, or tools depending on their needs and hardware capabilities. LLMFarm is particularly useful for developers and researchers experimenting with local AI systems, as it lowers the barrier to entry for running and testing models without extensive setup. ... -
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LLM Foundry
LLM training code for MosaicML foundation models
Introducing MPT-7B, the first entry in our MosaicML Foundation Series. MPT-7B is a transformer trained from scratch on 1T tokens of text and code. It is open source, available for commercial use, and matches the quality of LLaMA-7B. MPT-7B was trained on the MosaicML platform in 9.5 days with zero human intervention at a cost of ~$200k. Large language models (LLMs) are changing the world, but for those outside well-resourced industry labs, it can be extremely difficult to train and deploy... -
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ollama_manager_gui
A graphical manager for ollama that can manage your LLMs
This app will help install ollama and LLMs using the gui provided by this app. It checks for ollama when launched and if it doesn't exist it will help by bringing you to the ollama site for download. This app is heavily upgraded and now also works properly on Linux. It now has progress bars and many many many improvements. It can launch the LLM by clicking the link. it can launch multiple LLMs in separate windows. It can also remove an installed LLM. There is a confirmation... -
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LLMDataHub
Quick guide (especially) for trending instruction finetuning dataset
...The project aims to solve the challenge of discovering high-quality datasets by collecting resources that are otherwise scattered across multiple research communities and repositories. Each dataset entry typically includes information such as size, language coverage, intended use cases, and links to the original data sources. The repository focuses particularly on datasets useful for chatbot training, instruction-following tasks, and alignment training scenarios. By organizing these resources into a curated hub, the project helps researchers and developers identify the most relevant training corpora for building conversational AI systems. ... -
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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fastquant
Backtest and optimize your ML trading strategies with only 3 lines
...The project focuses on making backtesting accessible by providing a high-level interface that allows users to test investment strategies with only a few lines of code. It integrates historical market data sources and trading frameworks so that users can quickly build experiments without constructing complex data pipelines. The framework enables users to test common strategies such as moving average crossovers, momentum trading, and custom indicators on historical stock data. By automating data retrieval, strategy evaluation, and result visualization, the library reduces the barrier to entry for individuals interested in quantitative finance. ... -
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Neuro-comma
Punctuation restoration production-ready model for Russian language
This library was developed with the idea to help us to create punctuation restoration models to memorize trained parameters, data, training visualization, etc. The Library doesn't use any high-level frameworks, such as PyTorch-lightning or Keras, to reduce the level entry threshold. Feel free to fork this repo and edit model or dataset classes for your purposes. Our team always uses the latest version and features of Python. We started with Python 3.9, but realized, that there is no FastAPI image for Python 3.9. ... -
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Girls-In-AI
Free learning code series: Xiaobai's introduction to Python
Girls-In-AI is an educational repository created to encourage women and beginners to learn programming and artificial intelligence through accessible tutorials and practice materials. The project provides a collection of beginner-friendly learning resources covering Python programming, data analysis, machine learning, and deep learning topics. It aims to lower the barrier to entry for people who want to enter the field of artificial intelligence by offering structured learning paths and practical examples. The repository includes Jupyter notebooks, tutorials, and exercises that guide learners through topics such as data processing, machine learning model development, and Kaggle competition practice. ... -
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Spark Python Notebooks
Apache Spark & Python (pySpark) tutorials for Big Data Analysis
...Because Spark is widely used in industry for large-scale data processing, having these example notebooks lowers the barrier to entry for beginners and intermediate users alike. Users can run these notebooks locally or in cloud environments with notebooks like Jupyter or Zeppelin, making learning both flexible and contextual. -
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A Data Generator
A tool to generate synthetic test data useful to Record matchers
With growing amount of information from multiple sources it has become very hard to relate information to the correct real life entities. Record matching software try to solve this by machine learning techniques. To do this effectively, its necessary to train the record matcher with proper test data which is identical to real life data. Hence, there is a need for a data generator to create the synthetic data to be used for evaluating the quality and capability of record matching software. A data generator creates qualitative test data considering various the real life data glitches entered through various means like human data entry, voice dictation and data scanning. ... -
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Open Exchange (OpEx)
The open source Algorithmic Trading System
OpEx is an application suite that includes the main building blocks of commercial electronic trading systems. All OpEx applications run on distributed system architectures. -
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The purpose of this project is to develop ontology-based tools for the study of animal behavior (ethology). The goal is not to produce a general ontology or editor, but comparative methods and (behavior) data entry tools (ethontos and owlwatcher).
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*** This page is no longer used by the Dasher project - please see http://www.inference.phy.cam.ac.uk/dasher/ *** Dasher is a data entry interface incorporating language modelling and driven by continuous two-dimensional gestures, e.g. a mouse, a stylus
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